Circuits and methods for reducing an interference signal that spectrally overlaps a desired signal

ABSTRACT

Under one aspect, a method is provided for processing a received signal, the received signal including a desired signal and an interference signal that spectrally overlaps the desired signal. The method can include obtaining an amplitude of the received signal. The method also can include obtaining an average amplitude of the received signal based on at least one prior amplitude of the received signal. The method also can include subtracting the amplitude from the average amplitude to obtain an amplitude residual. The method also can include, based upon an absolute value of the amplitude residual being less than or equal to a first threshold, inputting the received signal into an interference suppression algorithm so as to generate a first output including the desired signal with reduced contribution from the interference signal.

FIELD OF THE INVENTION

This application relates to reducing an interference signal thatspectrally overlaps a desired signal.

BACKGROUND OF THE INVENTION

Receivers used in communication, navigation, radar, and other sensorapplications can suffer from intentional or unintentional interference.In such systems, it can be useful to use signal processing methods toreduce the effects of an interference signal from those of a desiredsignal.

In some systems, properties of the interference signal are not known apriori. In such cases, it can be desirable to use a blind technique, inwhich properties of the desired signal also may not necessarily be apriori known. A number of previously known blind single antennainterference suppression methods have been developed in the time domainand frequency-domain of a signal described in the complex in-phase (I)and quadrature (Q) domain. Some interference suppression techniquesexcise the interference in a domain in which the interference signal canbe separated from the desired signal, and selectively excised. Exceptfor time domain pulse blanking, such methods can assume a particularfrequency-domain or time/frequency transform, or utilize adaptive notchfiltering in which the interference can be removed by use of a notchfilter or frequency domain excision filter in the I/Q domain of thesignal. While such approaches potentially can work well for narrowbandinterference, such approaches can fail when the interference signalspectrally overlaps the desired signal, e.g., is spectrally matched tothe desired signal or has a bandwidth that overlaps some or all of thedesired signal. For example, previously known notch filtering orfrequency domain excision approaches can rely on the interference signalspectrally overlapping only a portion of the desired signal in the I/Qdomain. If the interference signal is spectrally matched to the desiredsignal, then such narrowband excision techniques will remove the desiredsignal as well as the interference.

Some approaches for reducing interference are non-blind, e.g., are basedupon a priori knowledge of the desired signal or of the interferencesignal. Some of such techniques are sometimes referred to as multi-userdetection (MUD) techniques. In such approaches, a copy of theinterference can be reconstructed in the receiver, including the preciseamplitude, phase, and timing of the interference. The reconstructedinterference then is subtracted from the incoming signal. Suchapproaches can require some time to track any interference that changesform or rapidly varies. Such variation can make it difficult orimpossible to reconstruct the interference in a receiver. Moreover,multiple interferers requires removal of each interferer in the presenceof the others making it very difficult to reconstruct precise phase,timing and amplitude of each interferer, One such technique to removethe effects of multiple interferers is successive interferencecancellation and will fail when the interferers get too close inamplitude.

Although adaptive antenna-array can be used to null out a matchedspectral or overlapping interference signal in the spatial domain, wherethe signal and interference are separated from one another alongdifferent spatial directions, spatial domain nulling and beam-formingapproaches can be costly and may not support a vast array of singleelement receiver implementations, such as handheld receivers.

Numerous approaches have been devised to mitigate strong constantenvelope co-channel interference received using a single receiveantenna. Maximum likelihood sequence estimation (MLSE) in the presenceof constant envelope interference is one known technique with areasonably simple hardware implementation. See, for example, Hui et al.,“Maximum Likelihood Sequence Estimation in the Presence of ConstantEnvelope Interference,” IEEE Vehicular Technology Conference 2:1060-1064 (2003), the entire contents of which are incorporated byreference herein. However, the MLSE algorithm or hardware must becustomized for the specific desired signal.

Another approach uses an adaptive filter to cancel interference causedby a constant envelope signal. This adaptive approach requires time toconverge, and even then a narrow band signal buried beneath a wide-bandstrong interference signal might not be recovered because the steadystate transfer function is frequency selective. See, for example,Ferrara, “A Method for Cancelling Interference from a Constant EnvelopeSignal,” IEEE Transactions on Acoustics, Speech, and Signal Processing33(1): 316-319 (1985), the entire contents of which are incorporated byreference herein.

A different approach maps a complex received signal into polarcoordinates. Then a fast Fourier transform (FFT) is computed on a blockof magnitude samples. The spectrum of the magnitude samples is thenexcised. An inverse FFT (iFFT) then transforms the excised spectrum intothe time domain. Such an approach does not require convergence time orany parameters of the weak signal, and can cancel many interferencesignals automatically. See, for example, Henttu, “A New InterferenceSuppression Algorithm Against Broadband Constant Envelope Interference,”IEEE Milcom 2: 742-746 (2000), the entire contents of which areincorporated by reference herein. However, such an approach can becomputationally complex, and also relies upon the interference having anapproximately constant envelope. However, the envelope of someinterference can vary by more than 3 dB.

A technique that may be used to mitigate multiple interferers, forexample, is successive interference cancellation. This technique,however, requires knowledge of each interferer and that the differencein power of each interferer is sufficient that the strongest interferercan be successively estimated, demodulated and subtracted from theremaining interferers, wherein the process is repeated until allinterferers are removed. Without prior knowledge of the interferers orif the interferers are too close in power, successive interferencecancellation will fail.

Joint demodulators can sometimes mitigate multiple interferers bydemodulating both signals together in a statistically optimum manner.Such techniques can be computationally complex and do not work well withmultiple interferers due to rapidly increasing complexity as the numberof interferers increases.

In either case, a demodulator for one desired signal type can thenrequire demodulators for many different undesired signal types. As newsignals emerge, algorithms must be updated. Unknown signals, such asproprietary waveforms, can render successive interference cancellationor joint demodulators impractical.

Thus, what is needed are improved systems and methods for reducinginterference.

SUMMARY OF THE INVENTION

Embodiments of the present invention provide circuits and methods forreducing an interference signal that spectrally overlaps a desiredsignal.

Under one aspect, a method is provided for processing a received signal,the received signal including a desired signal and an interferencesignal that spectrally overlaps the desired signal. The method caninclude obtaining an amplitude of the received signal. The method alsocan include obtaining an average amplitude of the received signal basedon at least one prior amplitude of the received signal. The method alsocan include subtracting the amplitude from the average amplitude toobtain an amplitude residual. The method also can include, based upon anabsolute value of the amplitude residual being less than or equal to afirst threshold, inputting the received signal into an interferencesuppression algorithm so as to generate a first output including thedesired signal with reduced contribution from the interference signal.

Some embodiments further include bypassing the interference suppressionalgorithm based upon the absolute value of the amplitude residual beinggreater than the first threshold. Some embodiments further include,based upon bypassing the interference suppression algorithm, generatinga second output equal to a predetermined value.

Some embodiments further include bypassing the interference suppressionalgorithm based upon the absolute value of the amplitude being less thana second threshold.

Some embodiments further include bypassing the interference suppressionalgorithm based upon a power of the received signal being less than asecond threshold.

Some embodiments further include bypassing the interference suppressionalgorithm based upon an interference to noise ratio of the receivedsignal being less than a second threshold. Some embodiments furtherinclude, based upon bypassing the interference suppression algorithm,generating a second output equal to the received signal.

In some embodiments, the first threshold is fixed.

In some embodiments, the first threshold varies as a function of theamplitude.

In some embodiments, the received signal includes a digitized timedomain signal, wherein the amplitude is that of a first sample of thedigitized time domain signal, and wherein the average amplitude is anaverage of the amplitudes of a plurality of samples of the digitizedtime domain signal.

Some embodiments further include obtaining a phase of the receivedsignal; and constructing an output based on the phase and the firstoutput.

In some embodiments, the interference suppression algorithm operates inan I/Q time domain of the received signal, in a frequency domain of thereceived signal, in an amplitude domain of the received signal, in anonlinear amplitude domain of the received signal, or in a combinationof more than one domain of the received signal.

Under another aspect, a circuit is provided for processing a receivedsignal, the received signal including a desired signal and aninterference signal that spectrally overlaps the desired signal. Thecircuit can include an amplitude circuit configured to: obtain anamplitude of the received signal; obtain an average amplitude of thereceived signal based on at least one prior amplitude of the receivedsignal; and subtract the amplitude from the average amplitude to obtainan amplitude residual. The circuit further can include an arithmeticcircuit configured to, based upon an absolute value of the amplituderesidual being less than or equal to a first threshold, input thereceived signal into an interference suppression algorithm so as togenerate a first output including the desired signal with reducedcontribution from the interference signal.

In some embodiments, the arithmetic circuit further is configured tobypass the interference suppression algorithm based upon the absolutevalue of the amplitude residual being greater than the first threshold.In some embodiments, the arithmetic circuit further is configured, basedupon bypassing the interference suppression algorithm, to generate asecond output equal to a predetermined value.

In some embodiments, the arithmetic circuit further is configured tobypass the interference suppression algorithm based upon the absolutevalue of the amplitude being less than a second threshold.

In some embodiments, the arithmetic circuit further is configured tobypass the interference suppression algorithm based upon a power of thereceived signal being less than a second threshold.

In some embodiments, the arithmetic circuit further is configured tobypass the interference suppression algorithm based upon an interferenceto noise ratio of the received signal being less than a secondthreshold.

In some embodiments, the arithmetic circuit further is configured, basedupon bypassing the interference suppression algorithm, to generate asecond output equal to the amplitude of the received signal.

In some embodiments, the first threshold is fixed.

In some embodiments, the first threshold varies as a function of thefirst amplitude.

In some embodiments, the received signal includes a digitized timedomain signal, wherein the amplitude is that of a first sample of thedigitized time domain signal, and wherein the average amplitude is anaverage of the amplitudes of a plurality of samples of the digitizedtime domain signal.

In some embodiments, the amplitude circuit further is configured toobtain a phase of the received signal; and the circuit further includesa signal construction circuit coupled to the amplitude circuit and tothe arithmetic circuit, the signal construction circuit being configuredto construct an output based on the phase and the first output.

In some embodiments, the interference suppression algorithm operates inan I/Q time domain of the received signal, in a frequency domain of thereceived signal, in an amplitude domain of the received signal, in anonlinear amplitude domain of the received signal, or in more than onedomain of the received signal.

Under another aspect, a method is provided for processing a receivedsignal including a desired signal and an interference signal thatspectrally overlaps the desired signal. The method can include obtainingamplitudes of samples of the received baseband signal. The method alsocan include applying a linear time domain filter to the amplitudes so asto obtain processed amplitudes of the samples with reduced interference.The method also can include generating an output signal with reducedinterference based on the processed amplitudes.

In some embodiments, the linear time domain filter includes a timedomain notch filter.

In some embodiments, the linear time domain filter includes a timedomain high pass filter.

In some embodiments, the method further includes estimating a signalquality metric; and adaptively adjusting one or more parameters of saidlinear time domain filter so as to optimize said signal quality metric.In some embodiments, optimizing said signal quality metric minimizes aninterference to noise power ratio (INR) or maximizes a carrier power tonoise spectral density ratio (C/No) or maximizes a signal power to noisepower ratio (SNR).

Under another aspect, a circuit is provided for processing a receivedbaseband signal including a desired signal and an interference signalthat spectrally overlaps the desired signal. The circuit can include anamplitude circuit configured to obtain amplitudes of samples of thereceived signal. The circuit also can include a linear time domainamplitude filter configured to receive the obtained amplitudes and tooutput processed amplitudes of the samples with reduced interference.The circuit also can include a signal construction circuit configured togenerate an output signal with reduced interference based on theprocessed amplitudes.

In some embodiments, the linear time domain filter includes a timedomain notch filter.

In some embodiments, the linear time domain filter includes a timedomain high pass filter.

In some embodiments, the circuit further includes circuitry configuredto estimate a signal quality metric; and circuitry configured toadaptively adjust one or more parameters of said linear time domainfilter so as to optimize said signal quality metric.

In some embodiments, optimizing said signal quality metric minimizes aninterference to noise power ratio (INR) or maximizes a carrier power tonoise spectral density ratio (C/No) or maximizes a signal power to noisepower ratio (SNR).

Under still another aspect, a method is provided for processing areceived signal, the received signal including a desired signal and aninterference signal that spectrally overlaps the desired signal. Themethod can include obtaining first non-unity power of amplitude of thereceived signal. The method also can include inputting the firstnon-unity power of the amplitude into an interference suppressionalgorithm to output a processed amplitude with reduced contribution fromthe interference signal. The method also can include generating anoutput signal with reduced contribution from the interference signalbased on the phase and the processed amplitude.

In some embodiments, the first non-unity power of the amplitude isobtained directly from the received signal.

In some embodiments, the first non-unity power of the amplitude isobtained by determining an amplitude of the received signal, and thentaking that amplitude to a first non-unity power.

In some embodiments, the interference suppression algorithm includesapplying a time domain notch filter.

In some embodiments, the interference suppression algorithm includesapplying a time domain high pass filter.

In some embodiments, the interference suppression algorithm includesapplying a Fourier transform based frequency excision algorithm.

In some embodiments, the method further includes applying interferencesuppression to the amplitude of the received signal, wherein theprocessed amplitude is based on the interference suppressed amplitude.

In some embodiments, the method further includes obtaining a secondnon-unity power of the amplitude, wherein the first non-unity power isdifferent than the second non-unity power; and applying interferencesuppression to the second non-unity power of the amplitude. Theprocessed amplitude can be based on the interference suppressed secondnon-unity power of the amplitude.

In some embodiments, the first non-unity power is ½, 2, ⅓, or 3.

Under another aspect, a circuit is provided for processing a receivedsignal, the received signal including a desired signal and aninterference signal that spectrally overlaps the desired signal. Thecircuit can include a non-unity circuit configured to obtain a firstnon-unity power of amplitude of the received signal. The circuit furthercan include an interference suppressor configured to apply aninterference suppression algorithm to the first non-unity power of theamplitude to output a processed amplitude with reduced contribution fromthe interference signal. The circuit further can include a signalconstruction circuit configured to generate an output signal withreduced contribution from the interference signal interference based onthe processed amplitude.

In some embodiments, the non-unity circuit is configured to obtain thefirst non-unity power of the amplitude directly from the receivedsignal.

In some embodiments, the non-unity circuit is configured to obtain thefirst non-unity power of the amplitude based on determining an amplitudeof the received signal, and then taking that amplitude to a firstnon-unity power.

In some embodiments, the interference suppressor includes a time domainnotch filter.

In some embodiments, the interference suppressor includes a time domainhigh pass filter.

In some embodiments, the interference suppressor includes a Fouriertransform based frequency domain excisor.

In some embodiments, the interference suppressor further is configuredto apply interference suppression to the amplitude of the receivedsignal, and to output the processed amplitude based on the interferencesuppressed amplitude.

In some embodiments, the non-unity circuit further is configured toobtain a second non-unity power of the amplitude, wherein the firstnon-unity power is different than the second non-unity power; and theinterference suppressor further is configured to apply interferencesuppression to the second non-unity power of the amplitude to output theprocessed amplitude based on the interference suppressed secondnon-unity power of the amplitude.

In some embodiments, the first non-unity power is ½, 2, ⅓, or 3.

Under still another aspect, a method is provided for processing samplesof a received signal, the received signal including a desired signal andan interference signal that spectrally overlaps the desired signal. Themethod can include obtaining amplitudes of the samples of the receivedsignal. The method also can include defining a plurality of clusters,each cluster of the plurality having a corresponding cluster amplitude.The method also can include assigning each sample of a first subset ofthe samples to one of the clusters based on the amplitude of that sampleand based on one or more of the cluster amplitudes. The method also caninclude suppressing contribution of interference to each sample of thefirst subset of the samples based on the amplitude of that sample andbased on the cluster amplitude of the cluster to which that sample isassigned so as to obtain a processed amplitude of that sample withreduced interference. The method also can include generating an outputsignal with reduced interference based on the processed amplitudes ofthe samples of the first subset of the samples.

In some embodiments, the method further includes determining thatcontribution of interference need not be suppressed for at least onesample of a second subset of the samples.

In some embodiments, the method further includes, based upon theamplitude of at least one of the samples of the second subset and athreshold, outputting a predetermined value as the processed amplitudeof that sample.

In some embodiments, the method further includes, based upon theamplitude of at least one of the samples of the second subset and athreshold, outputting the amplitude of that sample as the processedamplitude of that sample.

In some embodiments, said suppressing further comprises transformingsamples into a transform domain representation, excising at least aportion of the interference in the transform domain, and performing aninverse transform to obtain the processed amplitudes. In someembodiments, the transform is a Fourier transform. In some embodiments,the transform is a wavelet transform.

In some embodiments, said suppressing includes subtracting the amplitudeof that sample from the cluster amplitude of the cluster to which thatsample is assigned.

In some embodiments, the method further includes estimating each clusteramplitude over a period of time.

In some embodiments, said suppressing comprises subtracting theamplitude of that sample from the estimated cluster amplitude of thecluster to which that sample is assigned. In some embodiments,estimating the cluster amplitude of each cluster comprises averaging,over the period of time, the amplitudes of the samples assigned to thatcluster. In some embodiments, said averaging comprises using a finiteimpulse response (FIR) or infinite impulse response (IIR) type digitalfilter. In some embodiments, the FIR or IIR type digital filter receivesas input only the amplitudes of the samples assigned to thecorresponding cluster, and updates an output of the filter only when anew amplitude is assigned to the corresponding cluster. Some embodimentsfurther include compensating for the group delay of the FIR or IIR typefilter prior to performing the subtraction. In some embodiments, thefilter includes an IIR type filter, an output of which is generatedusing steps that include storing the cluster average into a randomaccess memory (RAM) at an address corresponding to the cluster; updatingthe respective cluster average every sample by reading a value of theaverage from the RAM; multiplying the read value of the average by acoefficient; adding the multiplied coefficient to a multiplied versionof the amplitude of that sample to produce the filter output; andre-writing the new cluster average back into RAM at the addresscorresponding to the cluster. In some embodiments, the filter includesan FIR moving average filter. In some embodiments, the FIR movingaverage filter is implemented as a recursive running sum.

Some embodiments include assigning each sample of the first subset ofthe samples to one of the clusters includes computing respective minimumdistances between the amplitude of that sample and a plurality of thecluster amplitudes, and assigning the sample to the cluster for whichthe minimum distance is the smallest.

Some embodiments include defining the clusters at a first time based ona histogram of the amplitudes of the samples of the received signal atthe first time. Some embodiments further include re-defining theclusters at a second time based on a histogram of the amplitudes of thesamples of the received signal at the second time.

Some embodiments include creating or destroying at least one cluster ormerging at least two clusters according to a set of rules. Someembodiments include measuring respective intra-cluster distances betweenpairs of clusters based on the cluster amplitudes of those clusters, andwherein the set of rules defines that based upon any two clusters havingan intra-cluster distance that is less than a threshold, those twoclusters are to be merged. In some embodiments, said merging includesaveraging the cluster amplitudes of those two clusters; deleting one ofthe two clusters; and assigning the average of the cluster amplitudes ofthose two clusters to the other of the two bins. Some embodimentsinclude comprising measuring a minimum distance between the amplitude ofat least one of the samples and at least a subset of the clusteramplitudes, and wherein the set of rules defines that based upon thesmallest minimum distance between that amplitude and any of the clusteramplitudes of the subset exceeding a threshold, a new cluster having acluster amplitude equal to the amplitude for that sample is to be added.

In some embodiments, said defining the plurality of clusters comprisespartitioning an available digital amplitude space into a plurality ofbins. In some embodiments, the bins are spaced approximately evenlyacross the available amplitude space. In some embodiments, the bins arespaced unevenly across the available amplitude space. Some embodimentsfurther include updating the number of bins and locations of bins basedupon one or more properties of the received signal.

Under another aspect, a circuit is provided for processing samples of areceived signal, the received signal including a desired signal and aninterference signal that spectrally overlaps the desired signal. Thecircuit can include an amplitude circuit configured to obtain amplitudesof samples of the received signal. The circuit further can include acluster definition circuit configured to define a plurality of clusters,each cluster of the plurality having a corresponding cluster amplitude.The circuit further can include a cluster assignment circuit configuredto assign each sample of a subset of the samples to one of the clustersbased on the amplitude of that sample and based on one or more of thecluster amplitudes. The circuit further can include an interferencesuppressor circuit configured to suppress interference to each sample ofthe first subset of the samples based on the amplitude of that sampleand based on the cluster amplitude of the cluster to which that sampleis assigned so as to obtain a processed amplitude of that sample withreduced interference. The circuit further can include a signalconstruction circuit configured to generate an output signal withreduced interference based on the processed amplitudes.

In some embodiments, the interference suppressor circuit further isconfigured to determine that contribution of interference need not besuppressed for at least one sample of a second subset of the samples. Insome embodiments, the interference suppressor circuit further isconfigured, based upon the amplitude of at least one of the samples ofthe second subset and a threshold, to output a predetermined value asthe processed amplitude of that sample. In some embodiments, theinterference suppressor circuit further is configured, based upon theamplitude of at least one of the samples of the second subset and athreshold, to output the amplitude of that sample as the processedamplitude of that sample.

In some embodiments, the interference suppressor circuit further isconfigured to transform samples into a transform domain representation,excise at least a portion of the interference in the transform domain,and perform an inverse transform to obtain the processed amplitudesamples. In some embodiments, the transform is a Fourier transform. Insome embodiments, the transform is a wavelet transform.

In some embodiments, the interference suppressor circuit further isconfigured to subtract the amplitude of that sample from the clusteramplitude of the cluster to which that sample is assigned.

In some embodiments, the cluster definition circuit further isconfigured to estimate each cluster amplitude over a period of time. Insome embodiments, the interference suppressor circuit further isconfigured to subtract the amplitude of that sample from the estimatedcluster amplitude of the cluster to which that sample is assigned. Insome embodiments, the cluster definition circuit is configured toestimate the cluster amplitude of each cluster based on averaging, overthe period of time, the amplitudes of the samples assigned to thatcluster. In some embodiments, the cluster definition circuit comprises afinite impulse response (FIR) or infinite impulse response (IIR) typedigital filter configured to perform said averaging. In someembodiments, the FIR or IIR type digital filter is configured to receiveas input only the amplitudes of the samples assigned to thecorresponding cluster, and to update an output of the filter based onlyupon a sample having a new amplitude being assigned to the correspondingcluster. In some embodiments, the interference suppressor circuitfurther is configured to compensate for the group delay of the FIR orIIR type filter prior to performing the subtraction. In someembodiments, the circuit further includes a random access memory (RAM),the filter includes an IIR type filter, and the cluster definitioncircuit is configured to generate an output of the filter using stepscomprising: storing the cluster average into a RAM at an addresscorresponding to the cluster; updating the respective cluster averageevery sample by reading a value of the average from the RAM; multiplyingthe read value of the average by a coefficient; adding the multipliedcoefficient to a multiplied version of the amplitude of that sample toproduce the filter output; and re-writing the new cluster average backinto RAM at the address corresponding to the cluster. In someembodiments, the filter includes an FIR moving average filter. In someembodiments, the FIR moving average filter is configured to implement arecursive running sum.

In some embodiments, the cluster assignment circuit is configured toassign each sample of the first subset of the samples to one of theclusters based on a respective minimum distance between the amplitude ofthat sample and a plurality of the cluster amplitudes, and to assign thesample to the cluster for which the minimum distance is the smallest.

In some embodiments, the cluster definition circuit is configured todefine the clusters at a first time based on a histogram of theamplitudes of the samples of the received signal at the first time. Insome embodiments, the cluster definition circuit is configured tore-define the clusters at a second time based on a histogram of theamplitudes of the samples of the received signal at the second time.

In some embodiments, the cluster definition circuit is configured tocreate or destroy at least one cluster or merging at least two clustersaccording to a set of rules.

In some embodiments, the cluster definition circuit further isconfigured to measure respective intra-cluster distances between pairsof clusters based on the cluster amplitudes of those clusters, andwherein the set of rules defines that based upon any two clusters havingan intra-cluster distance that is less than a threshold, those twoclusters are to be merged. In some embodiments, the cluster definitioncircuit is configured to merge two clusters using steps comprising:averaging the cluster amplitudes of those two clusters; deleting one ofthe two clusters; and assigning the average of the cluster amplitudes ofthose two clusters to the other of the two bins.

In some embodiments, the cluster definition circuit further isconfigured to measure a minimum distance between the amplitude of atleast one of the samples and at least a subset of the clusteramplitudes, and wherein the set of rules defines that based upon thesmallest minimum distance between that amplitude and any of the clusteramplitudes of the subset exceeding a threshold, a new cluster having acluster amplitude equal to the amplitude for that sample is to be added.

In some embodiments, the cluster definition circuit is configured todefine the plurality of clusters based on partitioning an availabledigital amplitude space into a plurality of bins. In some embodiments,the bins are spaced approximately evenly across the available amplitudespace. In some embodiments, the bins are spaced unevenly across theavailable amplitude space. In some embodiments, the cluster definitioncircuit is configured to update the number of bins and locations of binsbased upon one or more properties of the received signal.

BRIEF DESCRIPTION OF DRAWINGS

The patent or application file includes at least one drawing executed incolor. Copies of this patent or patent application publication withcolor drawing(s) will be provided by the Office upon request and paymentof the necessary fee.

FIG. 1A schematically illustrates a circuit for reducing an interferencesignal that spectrally overlaps a desired signal in a receiver,according to some embodiments of the present invention.

FIG. 1B schematically illustrates a circuit for reducing an interferencesignal that spectrally overlaps a desired signal in a interferencesuppression appliqué, according to some embodiments of the presentinvention.

FIG. 2A schematically illustrates an exemplary threshold circuit for usein reducing an interference signal that spectrally overlaps a desiredsignal by applying one or more thresholds to that signal, according tosome embodiments of the present invention.

FIG. 2B illustrates a method for reducing an interference signal thatspectrally overlaps a desired signal by applying one or more thresholdsto that signal, according to some embodiments of the present invention.

FIG. 2C schematically illustrates application of exemplary thresholds toan exemplary signal that includes an interference signal that spectrallyoverlaps a desired signal, according to some embodiments of the presentinvention.

FIG. 2D schematically illustrates selected components of an exemplarythreshold circuit for use in reducing an interference signal thatspectrally overlaps a desired signal by applying a first threshold tothat signal, according to some embodiments of the present invention.

FIG. 2E schematically illustrates selected components of an exemplarythreshold circuit for use in reducing an interference signal thatspectrally overlaps a desired signal by applying a first and a secondthreshold to that signal, according to some embodiments of the presentinvention.

FIG. 3A schematically illustrates an exemplary interference suppressioncircuit for use in reducing an interference signal that spectrallyoverlaps a desired signal based on a linear time domain amplitudefilter, according to some embodiments of the present invention.

FIG. 3B illustrates steps in an exemplary method for reducing aninterference signal that spectrally overlaps a desired signal based on alinear time domain amplitude filter, according to some embodiments ofthe present invention.

FIG. 3C schematically illustrates exemplary circuit componentsconfigured to apply exemplary thresholds to an exemplary signal thatincludes an interference signal that spectrally overlaps a desiredsignal, according to some embodiments of the present invention.

FIG. 3D schematically illustrates selected components of an exemplaryappliqué implementation for reducing an interference signal thatspectrally overlaps a desired signal based on a linear time domainamplitude filter, according to some embodiments of the presentinvention.

FIG. 3E schematically illustrates selected components of an alternativeexemplary appliqué implementation for reducing an interference signalthat spectrally overlaps a desired signal based on a linear time domainamplitude filter, according to some embodiments of the presentinvention.

FIG. 3F illustrates the spectrum of an example received spread spectrumsignal compared to that of noise and matched spectral interference,according to one non-limiting example of the present invention.

FIG. 3G illustrates the resultant frequency spectrum of the amplitudebefore and after applying a linear time domain filter to the examplesignal illustrated in FIG. 3F, according to one non-limiting example ofthe present invention.

FIG. 3H illustrates a comparison of the C/No for interferencesuppression based on applying a linear time domain filter to the examplesignal illustrated in FIG. 3F, according to one non-limiting example ofthe present invention.

FIG. 4A schematically illustrates an exemplary interference suppressioncircuit for use in reducing an interference signal that spectrallyoverlaps a desired signal based on a non-unity power of the amplitude ofthe signals, according to some embodiments of the present invention.

FIG. 4B illustrates steps in an exemplary method for reducing aninterference signal that spectrally overlaps a desired signal based on anon-unity power of the amplitude of the signals, according to someembodiments of the present invention.

FIG. 4C is a plot of the frequency spectra of components of an exemplaryreceived signal, according to one non-limiting example of the presentinvention.

FIG. 4D is a plot of the frequency spectra of the amplitude and thepower for the exemplary received signal of FIG. 4C, according to onenon-limiting example of the present invention.

FIG. 4E schematically illustrates selected components of an exemplaryinterference suppression circuit for use in reducing an interferencesignal that spectrally overlaps a desired signal based on a non-unitypower of the amplitude of the signals, according to some embodiments ofthe present invention.

FIG. 4F schematically illustrates selected components of anotherexemplary interference suppression circuit for use in reducing aninterference signal that spectrally overlaps a desired signal based on anon-unity power of the amplitude of the signals, according to someembodiments of the present invention.

FIG. 4G illustrates steps in another exemplary method for reducing aninterference signal that spectrally overlaps a desired signal based on anon-unity power of the amplitude of the signals, according to someembodiments of the present invention.

FIG. 4H schematically illustrates selected components of anotherexemplary interference suppression circuit for use in reducing aninterference signal that spectrally overlaps a desired signal based on anon-unity power of the amplitude of the signals, according to someembodiments of the present invention.

FIG. 4I schematically illustrates selected components of anotherexemplary interference suppression circuit for use in reducing aninterference signal that spectrally overlaps a desired signal based on anon-unity power of the amplitude of the signals, according to someembodiments of the present invention.

FIG. 4J illustrates steps in another exemplary method for reducing aninterference signal that spectrally overlaps a desired signal based on anon-unity power of the amplitude of the signals, according to someembodiments of the present invention.

FIG. 4K is a plot of the frequency spectra of the amplitude and thepower for the exemplary received signal of FIG. 4C after interferencesuppression using the method of FIG. 4G, according to one non-limitingexample of the present invention.

FIG. 4L illustrates a comparison of the C/No for interferencesuppression based on applying multiple domain interference suppressionusing the method of FIG. 4G to the example signal illustrated in FIG.4C, according to some embodiments of the present invention, according toone non-limiting example of the present invention.

FIG. 5A schematically illustrates an exemplary interference suppressioncircuit for use in reducing an interference signal that spectrallyoverlaps a desired signal based on clustering the amplitudes of thesignals, according to some embodiments of the present invention.

FIG. 5B illustrates steps in an exemplary method for reducing aninterference signal that spectrally overlaps a desired signal based onclustering the amplitudes of the signals, according to some embodimentsof the present invention.

FIG. 5C illustrates amplitudes as a function of sample number for thesum of four exemplary interference signals.

FIG. 5D schematically illustrates selected components of an exemplaryinterference suppression circuit for use in reducing an interferencesignal that spectrally overlaps a desired signal based on based onclustering the amplitudes of the signals, according to some embodimentsof the present invention.

FIGS. 5E-5F schematically illustrate exemplary appliqué implementationsfor reducing an interference signal that spectrally overlaps a desiredsignal based on clustering the amplitudes of the signals, according tosome embodiments of the present invention.

FIG. 5G schematically illustrates selected components of anotherexemplary interference suppression circuit for use in reducing aninterference signal that spectrally overlaps a desired signal based onbased on clustering the amplitudes of the signals, according to someembodiments of the present invention.

FIG. 5H schematically illustrates selected components of anotherexemplary interference suppression circuit for use in reducing aninterference signal that spectrally overlaps a desired signal based onbased on clustering the amplitudes of the signals, according to someembodiments of the present invention.

FIG. 5I illustrates steps in an exemplary method for initializingamplitude cluster values, according to some embodiments of the presentinvention.

FIG. 5J illustrates an example of output of the cluster initializationmethod illustrated in FIG. 5I, according to some embodiments of thepresent invention.

FIG. 5K illustrates an exemplary method of merging amplitude clusters,according to some embodiments of the present invention.

FIG. 5L illustrates an exemplary method of adding new amplitudeclusters, according to some embodiments of the present invention.

FIG. 5M illustrates steps in an exemplary method for initializing andupdating amplitude cluster values, according to some embodiments of thepresent invention.

FIG. 5N illustrates the simulated C/No for different sizes of bins in abinned cluster implementation, according to one non-limiting example ofthe present invention.

FIG. 5O illustrates the C/No for different exemplary interferencesuppression techniques, according to one non-limiting example of thepresent invention.

FIGS. 5P-5Q illustrate exemplary circuits for use in a binned clusterimplementation, according to some embodiments of the present invention.

DETAILED DESCRIPTION

Embodiments of the present invention provide circuits and methods forreducing an interference signal that spectrally overlaps a desiredsignal. For example, if the desired signal and the interference signalshare a channel, that is, if they spectrally overlap with one another,and if desired signal is much stronger than the interference signal,then the desired signal can be relatively easy to detect and demodulate.However, in some circumstances, the interference signal can make it hardto detect and demodulate the desired signal. As described in greaterdetail herein, the present circuits and methods need not requiredetailed knowledge of the desired signal or the interference signal, andas such, readily can be implemented in a variety of practicalapplications. For example, the present circuits and methods can use anysuitable combination of one or more of the interference reductioncircuits or methods provided herein so as to provide an output thatincludes the desired signal with reduced contribution from theinterference signal. Such circuits and methods can reduce interferencebased on any suitable combination of one or more of: estimating theamplitude of the interference signal; applying thresholds based on thedifference between the measured amplitudes and the estimatedinterference amplitude, applying a sliding window average finite impulseresponse (FIR) filter to the signal amplitude; using a linear timedomain amplitude filter; processing with a non-unity power of theamplitude of the signals; or clustering the amplitudes of the signals.

In the following discussions, the subscript k will be used to indicatethe kth value of the residual or amplitude respectively. Thisnomenclature can be applied to digital signal processing but embodimentsof the present invention can be implemented though analog signalprocessing circuitry as well as digital signal processing. In the caseof analog signal processing, the subscript k may be replaced with thecontinuous time variable t, as would be known to one skilled in the art.For example, the kth amplitude A_(k) can be replaced with the value ofthe amplitude at time t, A(t).

Circuits for Processing Signals Including Desired Signals andInterference Signals that Spectrally Overlap the Desired Signals

FIG. 1A schematically illustrates a circuit for reducing an interferencesignal that spectrally overlaps a desired signal in a receiver,according to some embodiments of the present invention. As illustratedin FIG. 1A, receiver 10 can include an antenna/analog conditioner 11configured to receive a signal that includes the interference signal andthe desired signal; optional analog-to-digital (A/D) converter 12;signal processor 13 configured to process the received signals in orderto perform conventional receiver functions such as synchronization,demodulation, decoding and other functions; and interference reductioncircuit 100 disposed therebetween. In the illustrated embodiment,interference reduction circuit 100 optionally includes threshold circuit110 connected to A/D converter 112; interference suppression circuit 120coupled to optional threshold circuit 110; and optional signalconstruction circuit 130 coupled to interference suppression circuit 120and coupled to signal processor 13. Signal processor 13 can beimplemented using digital or analog circuitry. Note that in embodimentsthat exclude A/D converter 12, antenna/analog conditioner 11 insteadsuitably can be connected to optional threshold circuit 110 or tointerference suppression circuit 120. In such embodiments, optionalthreshold circuit 110 or interference suppression circuit 120 can beimplemented using analog circuits. Interference suppression circuit 120,optional threshold circuit 110, and signal processor 130 also can beimplemented in various combinations of analog and/or digital circuitry.

Optional threshold circuit 110 can be configured so as to compute theamplitude, average amplitude, and amplitude residual determined from thedifference between the amplitude and the average amplitude, or optionalthreshold circuit 110 can be configured so as to accept the amplitudeand amplitude residual that is computed by interference suppressioncircuit 120 or some other circuit in receiver 10. Optional thresholdcircuit 110 can be configured so as to provide a gating signal tocontrol the signal values going into interference suppression circuit120 and/or can be configured so as to provide a second gating signal tobypass interference suppression circuit 120 based upon the amplitudebeing below a predetermined value. Optional threshold circuit 110 can beconfigured so as to provide a replacement signal that will set theoutput of interference suppression circuit 120 to a predetermined value.Optional threshold circuit 110 also can be configured so as to computeor accept signal power, signal to noise ratio, or interference to noisepower ratio from determined outside of optional threshold circuit 110 soas to trigger a second threshold as to whether or not interferencesuppression circuit 120 should be applied or bypassed.

Additionally, in embodiments that exclude optional threshold circuit110, interference suppression circuit 120 suitably can be connected toA/D converter 12 (if present) or to antenna/analog conditioner 11.Receiver 10 illustrated in FIG. 1A can include, but is not limited to, aglobal navigation satellite system receiver (GNSS) such as GPS, Glonass,Compass, or Galileo, a cellular wireless communications receiver, aWiFi, Bluetooth, or other radio frequency receiver, or a radar receiveror satellite communication system receiver.

Antenna/analog conditioner 11 illustrated in FIG. 1A can be configuredto wirelessly receive a signal that includes the desired signal and theinterference signal that spectrally overlaps the desired signal. In oneexample, antenna/analog conditioner 11 can be configured to receive thesignal, which can fall within a pre-defined spectral band, andantenna/analog conditioner 11 can include one or more filters configuredto block signals having frequencies that fall outside of this band.Appropriate antenna designs for a variety of signals in a variety ofcontexts, e.g., terrestrial, aircraft, or space-based antennas, areknown in the art. In some embodiments, antenna/analog conditioner 11 canbe or include a pre-existing structure to which inventive circuit 100can be coupled. Antenna/analog conditioner 11 also can include an inputradio frequency (RF) filter to select the bandwidth containing desiredsignal components and reject other signals at frequencies outside ofthat bandwidth, a low noise amplifier to establish the system noiselevel, and can contain one or more downconverters to translate the RFbandwidth containing the user signals into the bandwidth over which theoptional A/D converter 12 operates. Such components can be consideredtogether to constitute analog conditioning circuitry.

The received signal can be digital or analog, and can be in the timedomain or the frequency domain. For example, in some embodiments inwhich the present circuits and methods are used to reduce interferencefor GPS C/A code receivers, the desired signal can include a sum ofbinary-phase shift keyed (BPSK) modulated signals received at a powerlevel below the power level of the thermal noise present in the GPS C/Acode receiver. In such embodiments, the interference can include asignal which completely overlaps the desired signal. Such an exampleinterferer can be referred to as a matched spectral interferer. One typeof matched spectral C/A code interferer is a BPSK signal transmitted atthe same symbol rate of the C/A code (e.g., 1.023 Mchips/sec), orQPSK/QAM interference using the same symbol rate of the C/A code. Insome embodiments, the interference signal can partially spectrallyoverlap the signal, such as BPSK at lower or higher symbol rates thanthe desired signal. Another non-limiting example of an interferencesignal is a frequency modulated signal which sweeps a tone over thedesired signal bandwidth. FM swept-tone interference is a common type ofsignal used to disrupt GPS receivers in intentional GPS jammingequipment (see, e.g., Mitch et al., “Signal Characteristics of Civil GPSJammers,” Proceedings of the 24^(th) International Technical Meeting ofthe Satellite Division of the Institute of Navigation ION GNSS 2011,Portland Oreg., pp. 1907-1919, September 2011, the entire contents ofwhich are incorporated by reference herein).

As is known to one skilled in the art, other types of spectrallyoverlapping interference signals may also be present. These signals canbe modulated in a number of ways, including, but not limited to, AMmodulation, FM modulation, direct sequence spreading, frequency hoppedspreading, or phase shift keying.

The interference signal can have, but need not necessarily have, agreater power than that of the desired signal. In some embodiments, thepower of the interference signal can be significantly larger than thedesired signal, and can be anywhere from 10 times larger than thedesired signal (10 dB) to 1,000,000,000 times larger than the desiredsignal (90 dB). In other embodiments, the interference to signal powerratio can be greater than 1,000,000,000 (90 dB).

Optional A/D converter 12 can include an input port configured to becoupled to antenna/analog conditioner 11 via a suitable element (notspecifically illustrated), such that optional A/D converter 12 receivesthe signal received and suitably processed by antenna/analog conditioner11. The element connecting antenna/analog conditioner 11 and optionalA/D converter 12 can include a conductive element such as a coaxialcable, a transmission line, or any other suitable conductor configuredto transmit signals within a pre-defined spectral band fromantenna/analog conditioner 11 to A/D converter 12 via the input port.Note, however, that the element can include any path suitably configuredto transmit the signal from antenna/analog conditioner 11 to A/Dconverter 12 and need not necessarily include a continuous conductor,e.g., the element can include a capacitor or transformer.

Optional A/D converter 12 is configured to digitize and quantize thesignal that it receives from antenna/analog conditioner 11, and provideas output digitized samples of the signal. As known to those of skill inthe art of digital signal processing, A/D converters are commerciallyavailable devices that generate a digital version of an analog signal bysampling that signal at a specified rate. Note that in some embodiments,antenna/analog conditioner 11 can include its own A/D converterconfigured to digitize the received signal, or even can receive thesignal in a digital format. In embodiments including A/D converter 12,the A/D converter can provide the digitized samples as output tointerference reduction circuit 100, e.g., to optional threshold circuit110 or to interference suppression circuit 120, via an output port and asuitable path (not specifically illustrated). In one exemplaryembodiment, antenna/analog conditioner 11 includes an analog quadraturedownconverter, and A/D converter 12 includes two parallel A/D convertersthat are configured so as to provide digitized samples as output tointerference reduction circuit 100.

In the embodiment illustrated in FIG. 1A, optional threshold circuit 110is configured to receive the signal from optional A/D converter 12 viaan input port and any suitable path. Or, for example, optional thresholdcircuit 110 can be configured to receive the signal from antenna/analogconditioner 11 via an input port and any suitable path. In analogimplementations of the present circuits and methods, the A/D convertercan be omitted and threshold circuit 110 can be implemented using analogcircuitry. In such cases, the discrete time samples (represented by thesubscript k) can be replaced by a continuous time variable representedby the variable t.

Optional threshold circuit 110 can be configured to provide the signalto interference suppression circuit 120 based upon the amplitude of thesignal, e.g., in a manner such as described in greater detail below withreference to FIGS. 2A-2E. In alternative embodiments, optional thresholdcircuit 110 can be omitted, and interference suppression circuit 120 canbe configured to receive the signal from optional A/D converter 12 viaan input port and any suitable path, or from antenna/analog conditioner11 via an input port and any suitable path.

Interference suppression circuit 120 can be configured so as to reducethe contribution of the interference signal using any suitablecircuitry. For example, in some embodiments, interference suppressioncircuit 120 can be configured to reduce the interference signal based onusing a linear time domain amplitude filter, e.g., in a manner such asdescribed in greater detail below with reference to FIGS. 3A-3H. Asanother example, in some embodiments, interference suppression circuit120 can be configured to reduce the interference signal based on anon-unity power of the amplitude of the signals, e.g., in a manner suchas described in greater detail below with reference to FIGS. 4A-4L. Asanother example, in some embodiments, interference suppression circuit120 can be configured to reduce the interference signal based onclustering the amplitudes of the signals, e.g., in a manner such asdescribed in greater detail below with reference to FIGS. 5A-5Q. Anysuitable combination of two or more of such techniques can beimplemented using interference suppression circuit 120.

Optional signal construction circuit 130 is configured to receive one ormore outputs from interference suppression circuit 120 and, based onsuch output(s), to construct a signal that includes the desired signalwith reduced contribution from the interference signal as compared tothe signal received by antenna/analog conditioner 11. For example, insome embodiments, interference suppression circuit 120 can be configuredto obtain the amplitude and the phase of the received signal, and tomodify the amplitude so as to reduce contribution from the interferencesignal. Optional signal construction circuit 130 can be configured toreceive the phase and the modified amplitude from interferencesuppression circuit 120, and to construct an output signal based on thephase and the modified amplitude. In other embodiments, interferencesuppression circuit 120 can be configured so as to output a signalhaving phase and an amplitude with reduced contribution from theinterference signal, and signal construction circuit 130 can be omitted.

Signal processor 13 can be configured so as to receive the output frominterference reduction circuit 100, e.g., from interference suppressioncircuit 120 or from optional signal construction circuit 130, and can beconfigured so to extract the desired signal from the output of 120,which includes reduced contribution from the interference signal.

Note that optional A/D converter 12, optional threshold circuit 110,interference suppression circuit 120, and optional signal constructioncircuit 130 can be implemented using any suitable circuits or componentsknown in the art. For example, hardware circuits for performing A/Dconversion are readily commercially available. As another example,optional threshold circuit 110, interference suppression circuit 120,and optional signal construction circuit 130 can be implemented usingany suitable combination of arithmetic circuits that are known in theart for arithmetically operating on analog or digital signals (e.g., IIRfilter, FIR filter, subtractor, adder, multiplier, divider, or thelike).

Any such analog or digital hardware components suitably can be coupledtogether with any suitable paths, such as conductive elements ornon-conductive elements. Other circuits could be employed in the analogor digital domain including comparators or envelope detectors, as isknown to one skilled in the art. In other embodiments, thefunctionalities of one or more of optional A/D converter 12, optionalthreshold circuit 110, interference suppression circuit 120, andoptional signal construction circuit 130 can be provided by a suitablyprogrammed field-programmable gate array (FPGA), application-specificintegrated circuit (ASIC). FPGAs and ASICs are commercially available,and methods of programming same to achieve desired logical programmingare known in the art. In still other embodiments, the functionalities ofone or more of optional A/D converter 12, optional threshold circuit110, interference suppression circuit 120, and optional signalconstruction circuit 130 can be provided by a suitably programmedcomputer, e.g., a personal computer including a processor and anon-transitory computer-readable medium storing instructions to causethe processor to perform the steps of the present methods or toimplement the functionality of the present circuits. Alternatively, theprocessor can include a digital processor, such as a central processingunit (CPU) or graphics processor unit (GPU), or an analog processor.Additionally, note that circuitry other than optional threshold circuit110, interference suppression circuit 120, and optional signalconstruction circuit 130 can be used to provide interference reductioncircuit 100 with functionality analogous to that described herein.

In an alternative embodiment, interference suppression appliqué 10′illustrated in FIG. 1B includes some similar components as receiver 10illustrated in FIG. 1A. Interference suppression appliqué 10′ includesanalog conditioner/downconverter 11; optional A/D converter 12 which canbe configured similarly as optional A/D converter 12 described abovewith reference to FIG. 1A; optional threshold circuit 110 which can beconfigured similarly as optional threshold circuit 110 described abovewith reference to FIG. 1A; interference suppression circuit 120 whichcan be configured similarly as interference suppression circuit 120described above with reference to FIG. 1A; optional signal constructioncircuit 130 which can be configured similarly as signal constructioncircuit 130 described above with reference to FIG. 1A; optionaldigital-to-analog (D/A) converter 14; and upconverter/analogconditioner. Interference suppression appliqué can be inserted between areceiver's antenna and analog conditioner and configured so as tosuppress the effects of interference before it reaches an unmodifiedreceiver. For example, interference suppression appliqué 10 can beinserted between a GPS receiver antenna and an unmodified receiver orbetween a cellular base station antenna and an unmodified receiver. Ininterference suppression applique 10′, interference reduction circuit100 can be configured to provide its output to digital-to-analog (D/A)converter 14, which is configured to convert the output to the analogdomain. Upconverter and analog conditioner 15 are configured to receivethe analog output from D/A converter via a suitable path and an inputport, and to amplify and upconvert the analog output to an appropriatelevel expected by an unmodified receiver. As will be recognized by thoseskilled in the art, upconverter and analog conditioner 15 suitably caninclude an optional digital-to-analog converter and a frequencyupconverter to translate the user signals into an analog RF signal.Appropriate analog conditioner designs for a variety of signals in avariety of contexts, e.g., terrestrial, aircraft, or space-basedantennas, are known in the art.

Some exemplary circuits and methods for use in reducing interference incircuits such as described with reference to FIGS. 1A and 1B now will bedescribed.

Reducing Interference Based on Applying Thresholds to the Signals

FIG. 2A schematically illustrates an exemplary threshold circuit for usein reducing an interference signal that spectrally overlaps a desiredsignal by applying one or more thresholds to that signal, according tosome embodiments of the present invention. Threshold circuit 210illustrated in FIG. 2A includes one or more amplitude circuits 211 andarithmetic circuit 216. Optionally, the one or more amplitude circuits211 include an optional rectangular to polar converter (not specificallyillustrated), in which embodiments threshold circuit 210 also optionallyincludes a polar to rectangular converter (not specificallyillustrated).

Amplitude circuit(s) 211 can be configured so as to receive a signalincluding a desired signal and an interference signal that spectrallyoverlaps the desired signal. For example, referring to FIG. 1A,amplitude circuit(s) 211 can be configured so as to receive the signalin the analog domain from antenna/analog conditioner 11, or can beconfigured so as to receive digitized samples of the signal fromoptional A/D converter 12. Optionally, the received signal can include atime domain signal, or can include a frequency-domain signal.

Amplitude circuit(s) 211 can be configured to obtain an amplitude of thereceived signal. For example, in some embodiments, amplitude circuit(s)211 illustrated in FIG. 2A can include envelope detector 212, amplitudeaverager 213, delay circuit 214, and residual computation circuit 215.Envelope detector 212 can be configured so as to receive the signal,including the desired signal and the interference signal, fromantenna/analog conditioner 11 or optional A/D converter 12. Envelopedetector 212 can include suitable circuitry configured so as to detectan envelope of the signal, e.g., so as to detect the amplitude of thesignal at a given moment. Amplitude averager 213 can be configured so asto receive the envelope of the signal from envelope detector 212 and tocompute an average of the envelope of the signal, e.g., over apredetermined time or over a number of samples of the signal. In anonlimiting example, the input to amplitude averager 213 can be gatedsuch that certain values or samples at the output of envelope detector212 are not input into the amplitude averager 213. In this way thesecertain values or samples will not contribute to the average. Delaycircuit 214 can be configured so as to receive the signal from envelopedetector 212 and to delay the signal, e.g., to compensate for any delaycaused by the computation of the average amplitude by amplitude averager213. The delay block 214 is optional. Residual computation circuit 215can be configured so as to receive the delayed signal from delay circuit214 and the average amplitude 213, as so as to compute a residual value,e.g., an arithmetic difference between the amplitude (detected byenvelope detector 212) and the average amplitude (computed by amplitudeaverager 213). Additionally, amplitude circuit(s) 211 optionally can beconfigured to obtain a phase of the received signal. For example, insome embodiments, the received signal can be in rectangular coordinates,and amplitude circuit(s) 211 can include an optional rectangular topolar converter (not specifically illustrated) configured to obtain anamplitude and a phase of the received signal. Amplitude circuit 211 canbe coupled so as to provide the amplitude to arithmetic circuit 216,and, in embodiments in which the phase also is obtained, optionally canbe coupled so as to provide the phase to an optional polar torectangular converter (not specifically illustrated) of arithmeticcircuit 216. In a nonlimiting example, arithmetic circuit 216 can beconfigured to measure the size of the residual computed by residualcircuit 215 and compare it to a threshold so as to determine if certainsamples or values of the output of envelope detector 212 should be gatedor blocked from entering the amplitude averager 213.

For example, a signal can be described by s(t)=Re(Ae^(jθ)e^(jω))=Icos(ωt)−Q sin(ωt). I corresponds to the in-phase component of the signaland Q corresponds to the quadrature component of the signal. Envelopedetector 212 can be configured so as to compute the amplitude (envelope)from these components by:

A(t)=√{square root over (I ² +Q ²)}=√{square root over((I+jQ)×(I+jQ)*)}  (1)

The desired signal, which in some circumstances can be weak relative tothe interference, can be described by S_(w)(t)=I_(w)+jQ_(w). Theinterference signal, which in some circumstances can be strong relativeto the desired signal, can be described by S_(I)(t)=I_(I)+jQ_(w).Additionally, the noise in the circuit can be described byn(t)=n_(I)+jn_(Q).

The received signal can be expressed as the sumS(t)=S_(w)(t)+S_(I)(t)+n(t). Thus, the composite amplitude of S(t) canbe expressed as:

A(t)=√{square root over ((I _(I) +I _(w) +n _(I))²+(Q _(I) +Q _(w) +n_(Q))²)}  (2)

Equation (2) can be rewritten in terms of component amplitudes andexpressed as:

A(t)=√{square root over (A _(I) ² +A _(w) ² +A _(n) ²+2(I _(w) I _(I) +I_(I) n _(I) +I _(w) n _(I))+2(I _(w) I _(I) +I _(I) n _(I) +I _(w) n_(I)))}  (3)

In Equation (3), A_(I) corresponds to the amplitude of the interference,which can be strong relative to the amplitude A_(w) of the desiredsignal. In the case where the interference signal is significantlygreater than the amplitude of the noise or of the desired signal, e.g.,is over 1000 times greater than the amplitude of the noise or of thedesired signal, the amplitude of the received signal, A(t), obtained byenvelope detector 212 can be approximated as:

A(t)≅√{square root over (A _(I) ²)}=|A _(I)|  (4)

Amplitude averager 213 illustrated in FIG. 2A can be configured so as toobtain an average amplitude A(t) of the received signal based on atleast one prior amplitude of the received signal received from envelopedetector 212. For example, amplitude averager 213 can be configured soas to receive a stream of amplitudes from envelope detector 212, and canbe configured so as to obtain an average, e.g., a running average, ofthe amplitude of the received signal over a predetermined window oftime, or over a predetermined number of digitized samples of the signal(in embodiments in which the signal is digitized). Exemplary hardwareimplementations of amplitude averager 213 include suitably configuredinfinite impulse response (IIR) filters, finite impulse response (FIR)filters, and arithmetic circuits configured to calculate a weightedaverage of a signal over a predetermined window of time or over apredetermined number of samples.

Embodiments of the present invention can be implemented using discretetime sampled data in the digital domain or continuous time data in theanalog domain.

In some embodiments, the predetermined window of time can be defined tobe a fraction or multiple of the desired signal's signaling rate, forexample the C/A code chip/symbol duration of 1/1.023 MHz in theembodiments where the present circuits and methods can be used tosuppress GPS C/A code interference. Choosing a relatively long timewindow over which to average can increase the effectiveness of thesuppression algorithm in constant envelope interference. In someembodiments, the predetermined window of time can be defined to be theminimum fraction of the desired signal's symbol duration that permitsadequate suppression of constant envelope interference, so as to alsopermit the suppression of time varying amplitudes. In some embodiments,the minimum fraction can be a quarter of a desired signal symbol period,or half of a desired signal symbol period, or one symbol period, forexample. In some embodiments, the predetermined window of time or thepredetermined number of samples can be defined such that the amplitudeof the interference signal is constant, or approximately constant, overthat window or that number of samples (e.g., such that the amplitude ofthe interference signal varies by about 10% or less over the window orthat number of samples). Alternatively, the predetermined window of timeor the predetermined number of samples can be based on Cramer-Rao boundknown in the art.

Some constant envelope signals can have widely varying amplitudes whenreceived in actual receivers with finite bandwidth front ends. Forexample, FIG. 2C illustrates an exemplary signal that includes aninterference signal that spectrally overlaps a desired signal. Morespecifically, the signal illustrated in FIG. 2C corresponds to anon-ideally generated Binary Phase Shift Keying (BPSK) pseudorandomnoise (PRN) code interference signal that is spectrally matched to the1.023 MCPS GPS C/A code. Ideal BPSK signals have a constant amplitude,however a bandlimited or filtered BPSK signal can have amplitudevariation near the symbol transitions. An ideal BPSK signal transmittedfrom a transmitter, through a channel, and subsequently received at areceiver can experience effective filtering due to the combination ofthe transmitter frequency response, channel frequency response, andreceiver frequency response. FIG. 2C shows amplitude samples computed inreal time at a 122 million sample per second rate, and it can be seenthat although the average amplitude is approximately constant at a value1000, there are times near symbol transitions that the amplitudedeviates dramatically from this average as the symbol transitions from+1000 to −1000. These rapid variations in amplitude can negativelyaffect the estimate of the average amplitude, and can degradeperformance of the suppression algorithm if not mitigated. The averagingtime window can be selected so as to sample a suitable number of symbolsof the BPSK interferer. Note that although FIG. 2C illustrates just oneexample of a C/A code matched spectral interference signal, it should beappreciated that any communication, navigation, or sensor receiver cansuffer from interference of similar type, including but not limited to3G, 4G wireless systems, Bluetooth, or WiFi receivers, or other GPSreceivers such as the P(Y) code receivers or M-code receivers, orsatellite position system receivers including Galileo, Compass, andGlonass. Additionally, note that the thresholds illustrated in FIG. 2Care described elsewhere herein.

Referring back to FIG. 2A, residual computation circuit 215 can beconfigured to receive the average amplitude of the signal from amplitudeaverager 213, can be configured to receive the amplitude of the signal(optionally delayed by delay circuit 214) from envelope detector 212,and can be configured to subtract the amplitude from the averageamplitude to obtain an amplitude residual. In one nonlimiting example,the received signal includes a digitized time domain signal, theamplitude is that of a first sample of the digitized time domain signal,and the average amplitude is an average of the amplitudes of a pluralityof samples of the digitized time domain signal.

It should be appreciated that alternative embodiments of the presentinvention can be configured to employ a power residual instead of anamplitude residual as discussed below.

Additionally, or alternatively, residual computation circuit 215 can beconfigured to subtract the average amplitude from the amplitude, or canbe configured to subtract the amplitude from the average amplitude. Bothtechniques can provide an amplitude residual which can be used infurther processing to suppress the interference and recover the desiredsignal.

In some embodiments, arithmetic circuit 216 illustrated in FIG. 2A canbe configured so as to receive the amplitude residual from residualcomputation circuit 215 and can be configured, based upon an absolutevalue of the amplitude residual being less than or equal to a firstthreshold, to input the received signal into an interference suppressionalgorithm so as to generate a first output including the desired signalwith reduced contribution from the interference signal. For example,referring again to FIGS. 1A and 1B, optional threshold circuit 110 canbe coupled so as to input the received signal (or the amplitude thereof)to interference suppression circuit 120, which can be configured so asto generate an output including the desired signal with reducedcontribution from the interference signal. Exemplary interferencesuppression circuits and methods are provided elsewhere herein, althoughit should be appreciated that any suitable interference suppressiontechnique can be used. One exemplary interference suppression algorithmsuitable for use is that described in U.S. patent application Ser. No.14/262,532, filed Apr. 25, 2014 and entitled “Systems and Methods forReducing a Relatively High Power, Approximately Constant EnvelopeInterference Signal that Spectrally Overlaps a Relatively Low PowerDesired Signal,” the entire contents of which are incorporated byreference herein. Other interference suppression algorithms include, butare not limited to, those described in the following references, theentire contents of each of which are incorporated by reference herein:Przyjemski et al., “GPS Antijam Enhancement Techniques,” Proceedings ofthe 49th Annual Meeting of The Institute of Navigation (1993), Jun.21-23, 1993, Royal Sonesta Hotel, Cambridge, Mass.; Henttu, “A newinterference suppression algorithm against broadband Constant envelopeinterference,” MILCOM 2000, 21st Century Military CommunicationsConference Proceedings Vol 2.; and Amoroso, “Adaptive AID Converter toSuppress CW Interference in DSPN Spread-Spectrum Communications,” IEEETransactions On Communications, Vol. COM-31, No. 10, October 1983.

Illustratively, the first threshold can be selected such that foramplitude residuals above the threshold, the expected performance of theinterference suppression algorithm can produce a more degraded outputsignal than by not disabling the input to the interference suppressionalgorithm when the threshold is exceeded. Additionally, the firstthreshold can be selected such that for amplitude residuals less than orequal to the threshold, the expected performance of the suppressionalgorithm can be improved relative to the case of not thresholding theinput based on the amplitude residual. For example, in some embodiments,arithmetic circuit 216 illustrated in FIG. 2A can be configured tobypass the interference suppression algorithm, e.g., can be configuredto bypass interference suppression circuit 120 illustrated in FIGS.1A-1B, based upon the absolute value of the amplitude residual beinggreater than the first threshold. Illustratively, arithmetic circuit 216can be configured, based upon bypassing the interference suppressionalgorithm, to generate a second output equal to a predetermined value.In one example, the predetermined value can be zero, although anysuitable value can be used. Arithmetic circuit 216 can provide such asecond output to signal construction circuit 130 illustrated in FIGS.1A-1B. Alternatively, arithmetic circuit 216 can be configured toprovide the second output to interference suppression circuit 120, whichcan be configured so as to pass through the second output to signalconstruction circuit 130 and signal processor(s) 13 illustrated in FIG.1A or D/A converter 14 illustrated in FIG. 1B.

Optionally, arithmetic circuit 216 can be configured to bypass theinterference suppression algorithm based upon the absolute value of theamplitude being less than a second threshold. For example, the secondthreshold can be selected such that for amplitude values below thesecond threshold, the desired signal is sufficiently strong relative tothe interference signal that interference suppression may not be neededin order to recover the desired signal. In one example, arithmeticcircuit 216 can be configured, based upon bypassing the interferencesuppression algorithm, to generate a third output equal to the amplitudeof the received signal.

Alternatively, the interference suppression algorithm can be bypassedbased upon the signal to noise level being greater than the secondthreshold. Moreover, the interference suppression algorithm also can bebypassed based upon the total power or interference to noise level beingbelow the second threshold. In such cases, the received signal power cansufficiently strong relative to the interference that interferencesuppression is not necessarily useful or efficient.

Arithmetic circuit 216 can be configured so as to provide such a thirdoutput to signal construction circuit 130 illustrated in FIGS. 1A-1B.Alternatively, arithmetic circuit 216 can be configured to provide thethird output to interference suppression circuit 120, which can beconfigured so as to pass through the third output to signal constructioncircuit 130 and signal processor 13 illustrated in FIG. 1A or D/Aconverter 14 illustrated in FIG. 1B. In some embodiments, signalconstruction circuit 130 is configured so as to construct a compositerecovered signal that includes one or more segments corresponding to thefirst output of arithmetic circuit 216, one or more segmentscorresponding to the second output of arithmetic circuit 216, andoptionally also includes one or more segments corresponding to the thirdoutput of arithmetic circuit 216.

It will be apparent to those skilled in the art that the first thresholdcan be applied to the amplitude residual signal (e.g., after subtractionby residual computation circuit 215), or can be equivalently appliedprior to subtraction on both the amplitude signal obtained by envelopedetector 212 and the averaged amplitude signal obtained by amplitudeaverager 213. For example, assume a residual amplitude signal R isproduced by residual computation circuit 215 subtracting an amplitudeestimate A_(e) from an (optionally delayed by delay circuit 214) signalA_(d), therefore R=A_(d)−A_(e). Assume for illustrative purposes thatTH1 is set to 100, and is applied to the absolute value of residual R,and that some logic circuit (e.g., arithmetic circuit 216) operatesbased upon whether or not the absolute value of R is less than TH1,e.g., whether or not |R| is less than 100 in one non-limiting example.An alternate implementation of threshold circuit 110 can be configuredso as to apply TH1 to A_(d) (obtained by envelope detector 212 andoptionally delayed by delay circuit 214) and A_(e) (obtained byamplitude averager 213) directly. In one non-limiting example, such anapplication of TH1 can be accomplished by ensuring thatA_(d)<(A_(e)+100) and A_(d)<(A_(e)−100). Also, a similar embodiment maybe constructed when the thresholds are not constant but insteadfunctions of the averaged amplitude estimate, for example if they aresome scaled version of the average amplitude.

In some embodiments, one or both of the first threshold and the secondthreshold are fixed. Alternatively, one or more of the first thresholdand the second threshold can vary, e.g., can vary as a function of theamplitude of the signal or as a function of the amplitude's deviationfrom a constant value, for example, the threshold may be varied inresponse to the measured peak to average power ratio.

Denote the input sample amplitude as “A_(k)” to arithmetic circuit 216,and denote the output of arithmetic circuit 216 as “A_(k)′”. Arithmeticcircuit 216 can be configured to use a first threshold (TH1) todetermine the allowable deviation between the amplitude of the inputsample amplitude A_(k) and the average amplitude of the received signal,e.g., the k_(th) estimate of the interference signal under theapproximation of Equation (4). The k^(th) amplitude residual aftersubtraction can be expressed as R_(k), and the kth output, denoted hereas A_(k)′, can be set to R_(k) based upon the absolute value of the kthamplitude residual being less than TH1. Otherwise, the output value canbe set equal to a predetermined value, A_(k)′=A₀:

If |R _(k) |<TH1,A _(k) ′=R _(k), Else A′ _(k) =A ₀  (5)

The predetermined value A₀ can be zero or some other value such as theaverage of the last several amplitude values.

It should also be appreciated that in some embodiments the residual R(or R_(k) in a discrete time version) may be determined from differencesin the power and the average power, so that interference suppressioncircuit 120 is triggered by a power residual instead of an amplituderesidual.

The first threshold (TH1) can be used to determine the allowabledeviation between the amplitude of the input amplitude signal and theaverage amplitude of the received signal or the allowable deviationbetween other quantities like input power and average power of thereceived signal. Threshold TH1 can be determined according to thetolerable loss, L, in signal to noise ratio (SNR). As one nonlimitingexample, TH1 can be selected so as to guarantee that the loss in SNR dueto errors in the estimate of the interference signal (e.g., the averageamplitude of the received signal under the approximation of Equation(4)) is less than or equal to 10 dB or other desired value.Alternatively, as another nonlimiting example, TH1 can be selected sothat the loss in received carrier power to noise power spectral densityratio, C/N₀ in dBW/Hz, is less than or equal to 10 dB or other desiredvalue. In still another nonlimiting example, TH1 can be selected so asto maximize the average SNR of the desired signal or to minimize ameasured jammer to noise ratio, or both. For example, a leastmean-square (LMS) algorithm, or other suitable minimization algorithm,can adapt one or both of TH1 and TH2 to maximize the SNR of the desiredsignal, or to minimize the measured interference to noise ratio (INR).Such maximization or minimization can be performed, for example, using ametric such as the measured interference to signal ratio (ISR) or themeasured INR.

In another example, arithmetic circuit 216 optionally can include anaveraging filter that is be “gated” at the input so as to prevent theamplitude values that do not meet a threshold criteria from contributingto the average amplitude of the received signal, e.g., the estimate ofthe interference signal under the approximation of Equation (4). Forexample, in embodiments in which a FIR filter is used to average theamplitude signal, the filter input optionally can be gated so that onlythose input amplitude signal values which produce amplitude residualvalues less than TH1 can contribute to the average. Similar gating canbe used to prevent the amplitude of a given sample from creating anerror in the current amplitude estimate for alternative filterimplementations, such as IIR filters, integrate and dump filters, orother filters that can be used to obtain the average amplitude of thereceived signal, e.g., the estimate of the interference signal under theapproximation of Equation (4).

In another non-limiting example, the second threshold (TH2) can beselected so that the interference suppression algorithm is bypassed whenthe amplitude values are less than a second threshold. Referring toEquations (1)-(4) above, based upon inputting to arithmetic circuit 216the k^(th) amplitude value A_(k), arithmetic circuit 216 suitably can beconfigured so as to output a modified amplitude A′_(k) based on:

if A _(k) <TH2,A _(k) =A _(k)′  (6).

In other words, in this example, do not apply interference suppressionbased upon the amplitude value being less than a predetermined value(TH2).

FIG. 2D schematically illustrates selected components of an exemplarythreshold circuit for use in reducing an interference signal thatspectrally overlaps a desired signal by applying a first threshold tothat signal, e.g., shows an exemplary circuit of such filter gating.Similar gating circuitry can be used so as to prevent a given inputamplitude sample that is less than TH2 from contributing to the averageamplitude of the received signal, e.g., the estimate of the interferencesignal under the approximation of Equation (4). Gating the input samplesin this way can provide significant improvement in estimating theinterference signal under the approximation of Equation (4), e.g., forsamples in which the amplitude of the interference signal varies fasterthan the filter response time. For example, interference that isimpulsive in nature can be expected not to degrade the performance ofthe filter estimates of the interference signal under the approximationof Equation (4) that otherwise can be caused by changes in interferencethat are significantly faster than the averaging time of the filter.

FIG. 2B illustrates a method 200 for reducing an interference signalthat spectrally overlaps a desired signal by applying one or morethresholds to that signal, according to some embodiments of the presentinvention. The received signal can include a desired signal and aninterference signal that spectrally overlaps the desired signal.Exemplary method 200 illustrated in FIG. 2B can include obtaining anamplitude of the received signal (step 201). For example, envelopedetector 212 of amplitude circuit(s) 211 such as described above withreference to FIG. 2A can obtain the amplitude of the received signal,and optionally can include rectangular to polar converter 212.

Exemplary method 200 illustrated in FIG. 2B further can includeobtaining an average amplitude of the received signal based on at leastone prior amplitude of the received signal (step 202). For example,amplitude averager 213 of amplitude circuit(s) 211 such as describedabove with reference to FIG. 2A can obtain an average amplitude of thereceived signal.

Exemplary method 200 illustrated in FIG. 2B also can include subtractingthe amplitude from the average amplitude to obtain an amplitude residual(step 203). For example, residual computation circuit 215 illustrated inFIG. 2A can obtain the amplitude of the received signal from envelopedetector 212, optionally delayed by delay 214, can obtain the averageamplitude from amplitude averager 213, and can subtract the amplitudefrom the average amplitude.

Exemplary method 200 further can include, based upon an absolute valueof the amplitude residual being less than a first threshold, inputtingthe received signal into an interference suppression algorithm so as togenerate a first output including the desired signal with reducedcontribution from the interference signal (step 204). For example,arithmetic circuit 216 such as described above with reference to FIG. 2Acan be configured so as to implement step 204. In one nonlimitingexample, the received signal includes a digitized time domain signal,the amplitude is that of a first sample of the digitized time domainsignal, and the average amplitude is an average of the amplitudes of aplurality of samples of the digitized time domain signal.

Optionally, method 200 illustrated in FIG. 2B also can include bypassingthe interference suppression algorithm based upon the absolute value ofthe amplitude residual being greater than the first threshold in amanner analogous to that described above with reference to FIG. 2A. Forexample, arithmetic circuit 216 can be configured so as to perform suchbypassing in a manner such as described above with reference to FIG. 2A.Illustratively, method 200 further can include, based upon bypassing theinterference suppression algorithm, generating a second output equal toa predetermined value in a manner analogous to that described above withreference to FIG. 2A.

Optionally, method 200 illustrated in FIG. 2B also can include bypassingthe interference suppression algorithm based upon the absolute value ofthe amplitude being less than a second threshold in a manner analogousto that described above with reference to FIG. 2A. For example,arithmetic circuit 216 can be configured so as to perform such bypassingin a manner such as described above with reference to FIG. 2A.Illustratively, method 200 further can include, based upon bypassing theinterference suppression algorithm, generating a third output equal tothe amplitude of the received signal in a manner analogous to thatdescribed above with reference to FIG. 2A. Exemplary interferencesuppression algorithms are provided elsewhere herein. As noted above,the first threshold or the second threshold, or both, can be fixed, orcan vary as a function of the first amplitude.

In some embodiments, method 200 illustrated in FIG. 2B can includeobtaining a phase of the received signal; and constructing an outputbased on the phase and the first output. For example, amplitude circuit211 illustrated in FIG. 2A can provide the phase of the received signalto signal construction circuit 130, and arithmetic circuit 216 can beconfigured so as to provide the first output (and optional second andthird outputs, if present) to signal construction circuit 130illustrated in FIGS. 1A-1B for use in constructing an output signalbased on the phase and the first (and optional second and third)outputs.

FIG. 2D schematically illustrates selected components of an exemplarythreshold circuit for use in reducing an interference signal thatspectrally overlaps a desired signal by applying a first threshold tothat signal, according to some embodiments of the present invention. Inthe exemplary embodiment illustrated in FIG. 2D, the first threshold canbe applied at the input of the interference suppression circuit. Anoutput amplitude residual R_(o) can be created by subtracting an averageof the input amplitude A_(e) by an (optionally delayed) input amplitudesignal A_(d). A second input amplitude residual R_(i) can be created bysubtracting an average of the input amplitude A_(e) by the inputamplitude A. Based upon the absolute value of the residual R_(i) beingless than the first threshold TH1, then, the amplitude can be input intothe averaging circuit, and after an optional delay corresponding to theoptional delay of the signal A_(d), residual R_(o) is passed to theoutput Y for further processing. Based on the absolute value of residualR_(i) being greater than (or equal to) TH1, the input amplitude whichcaused this large residual can be blocked from the averagingcomputation, and after an optional delay, a constant value can be sentto the output Y. In FIG. 2D the constant value is zero for illustrativepurposes; other values suitable can be used.

FIG. 2E schematically illustrates selected components of an exemplarythreshold circuit for use in reducing an interference signal thatspectrally overlaps a desired signal by applying a first and secondthreshold to that signal, according to some embodiments of the presentinvention. In the exemplary embodiment illustrated in FIG. 2E, the firstand second threshold can be applied at the input of the interferencesuppression circuit. An output amplitude residual R_(o) can be createdby subtracting an average of the input amplitude A_(e) by an (optionallydelayed) input amplitude signal A_(d). A second input amplitude residualR_(i) is created by subtracting an average of the input amplitude A_(e)by the input amplitude A. Based upon the input amplitude A being lessthan a second threshold TH2, then that input amplitude can be, after anoptional delay (corresponding to the optional delay of the signal A_(d),residual R_(o)), passed to the output. For example, TH2 can be set suchthat based upon the interference being sufficiently low, suppression isnot necessary for that input amplitude value. Based upon the absolutevalue of the residual R_(i) being less than the first threshold TH1,then the amplitude can be input into the averaging circuit, and after anoptional delay (corresponding to the optional delay of the signalA_(d),) residual R_(o) can be passed to the output Y for furtherprocessing. Based upon none of these conditions being met, e,g., basedupon |R_(i)| being larger than TH1, the input amplitude which causedthis large residual can be blocked from the averaging computation, andafter an optional delay, a constant is sent to the output Y. In FIG. 2E,the constant is zero for illustrative purposes; other values suitablycan be used.

In an alternative implementation, the first and optional secondthresholds and integration period parameters can be adapted based on thecharacteristics of the measured signal and noise parameters in a manneranalogous to that described in U.S. Pat. No. 8,515,335, the entirecontents of which are incorporated by reference herein.

Reducing Interference Based on Using a Linear Time Domain Filter in theAmplitude Domain

As noted above with reference to FIGS. 1A-1B, interference suppressioncircuit 120 can be configured so as to receive a signal that includes adesired signal and an interference signal that spectrally overlaps thedesired signal, and to reduce the contribution of the interferencesignal using any suitable circuitry. For example, in some embodiments,interference suppression circuit 120 can be configured to reduce theinterference signal based on using a linear time domain amplitudefilter, e.g., in a manner such as described with reference to FIGS.3A-3H. Interference suppression circuit 120 suitably can receive thesignal from optional threshold circuit 110, from A/D converter 12, fromantenna/analog conditioner 11 or any other suitable source. Althoughinterference suppression circuit 120 is compatible with optionalthreshold circuit 110, note that threshold circuit 110 suitably can beomitted.

FIG. 3A schematically illustrates an exemplary interference suppressioncircuit for use in reducing an interference signal that spectrallyoverlaps a desired signal based on a linear time domain amplitudefilter, with optional filter adaptation, according to some embodimentsof the present invention. Interference suppression circuit 320illustrated in FIG. 3A includes optional rectangular to polar converter321, envelope detector 322, linear time domain amplitude filter 323,optional signal quality estimator 324, optional signal constructioncircuit 325, and optional filter parameter adapter 326. In someembodiments, linear time domain amplitude filter 323 can be coupled tooptional threshold circuit 110 or 210 via a suitable pathway so as toreceive amplitudes of the received signal from optional thresholdcircuit 110 or 210. In other embodiments, interference suppressioncircuit 320 can include envelope detector 322 configured to receive thesignal from optional threshold circuit 110, from A/D converter 12, fromantenna/analog conditioner 11, or from any other suitable source, andconfigured to obtain an amplitude of the received signal. Additionally,the envelope detector 322 optionally can be configured to obtain a phaseof the received signal.

For example, in some embodiments, the received signal can be inrectangular coordinates, and interference suppression circuit 320 caninclude an optional rectangular to polar converter 321 configured toobtain an amplitude and a phase of the received signal. Envelopedetector 322 can be coupled so as to provide the amplitude to lineartime domain amplitude filter 323, and, in embodiments in which the phasealso is obtained, optionally can be coupled so as to provide the phaseto signal construction circuit 130 illustrated in FIGS. 1A-1B or tooptional signal construction circuit 325 illustrated in FIG. 3A. In onenonlimiting embodiment, the received signal is a digitized basebandsignal, and the amplitude circuit is configured to obtain amplitudes andphases of the complex in-phase and quadrature samples of the receivedbaseband signal. Other embodiments may perform signal processing at onthe intermediate frequency or radio frequency representation of thesignal.

In the exemplary interference suppression circuit in FIG. 3A, lineartime domain filter 323 can be configured to as to estimate the amplitudeof the interference in the received signal. Some exemplary embodimentsof estimating the amplitude of the interference are provided furtherabove with reference to FIGS. 2A-2E. In one nonlimiting embodiment,linear time domain amplitude filter 323 is configured to receive theobtained amplitudes and to output processed amplitudes of the sampleswith reduced interference. For example, in some embodiments, linear timedomain filter 323 includes a time domain notch filter. In someembodiments, linear time domain filter 323 includes a plurality of timedomain notch filters, at least one of said time domain notch filtersbeing centered at DC (e.g., a high pass filter). Illustratively, anapproximately constant envelope interference signal will have arelatively large DC component in the amplitude domain. The bandwidth ofthis DC component will depend on how rapidly the envelope varies overtime. A high pass filter (e.g., a notch filter centered at DC) with acutoff bandwidth set to the approximate bandwidth of the interferenceenvelope variation can remove this large amplitude at DC withoutremoving additional amplitude information.

In some embodiments, linear time domain filter 323 operates directly onreal-valued amplitude samples of the signal, A_(k)=√{square root over(I_(k) ²+Q_(k) ²)}, Linear time domain filter 323 can be unlike an I/Qnotch filter that instead would operate on the I and Q samples directly,z_(k)=I_(k)+jQ_(k). By operating in the amplitude domain, the presentlinear time domain filter 323 can filter out interference componentswithout filtering away the desired signal, even for an interferencesignal that is spectrally matched to the desired signal. For example,constant envelope signals, when converted to the amplitude domain, havea strong zero-frequency (DC) component. A high pass filter can be viewedas a differentiator. Therefore a high pass filter (e.g., a notch filtercentered at DC) in the amplitude domain can be used to perform anoperation analogous to that performed in steps 202 and 203 of method 200described above with reference to FIG. 2B, e.g., the high pass filtercan be configured so as to remove the low frequency constant amplitudecomponent. Whereas some embodiments of steps 202 and 203 of method 200(with reference to FIG. 2B) can explicitly estimate (e.g., viaaveraging) and then subtract the low-frequency content, a high passfilter removes the low frequency content in one filtering operation.

In some embodiments, interference suppression circuit 320 also includescircuitry, e.g., optional filter parameter adapter 326, configured toadaptively adjust linear time domain filter 323, e.g., so as to minimizean interference to noise ratio (INR) or to maximize a carrier power tonoise spectral density ratio (C/No) or a signal to noise ratio (SNR).Illustratively, such circuitry can be configured so as to use a LMS orsimilar algorithm so as automatically to minimize one or more of suchmetrics, which can be estimated by a receiver, digital processor, or thelike. The filter parameters also can be manually adjusted so as toenhance performance for a given interference type. Optional filterparameter adapter 326 can be coupled to optional signal constructioncircuit 325 and configured so as to adaptively adjust linear time domainfilter 323 based on one or more characteristics of the signal, e.g., oneor more metrics of signal quality such as estimated by optional signalquality estimator 324 coupled between linear time domain filter 323 andoptional signal construction circuit 325. For example, optional signalquality estimator 324 can be configured so as to estimate a signalquality metric; and optional filter parameter adaptor 325 can beconfigured so as to adaptively adjust one or more parameters of lineartime domain filter 323 so as to optimize said signal quality metric.

In some embodiments, interference suppression circuit 320 illustrated inFIG. 3A is coupled to optional signal construction circuit 325configured to generate an output baseband signal with reducedinterference based on the phases and the processed amplitudes of thesamples. In some embodiments, signal construction circuit 325illustrated in FIG. 3A or signal construction circuit 130 illustrated inFIGS. 1A-1B can be coupled to linear time-domain amplitude filter 323 soas to receive therefrom processed amplitudes of the samples with reducedinterference, and can be coupled to an amplitude circuit (e.g.,amplitude circuit(s) 211 such as described above with reference to FIG.2A, optional rectangular to polar converter 321 of interferencesuppression circuit 320) so as to receive therefrom phases of thosesamples, and can be configured to generate an output baseband signalbased thereon.

Examples in which interference is reduced based on an estimate of theamplitude of the interference are provided elsewhere herein, e.g., withreference to FIGS. 2A-2E. It is anticipated that embodiments that reduceor obviate the need to obtain an estimate of the amplitude of theinterference, e.g., embodiments in which interference is reduced basedon using a linear time domain filter, can effectively be applied incases where an estimate of the amplitude of the interference may bedifficult to obtain, such as at low ISR values. Additionally, thepresent linear time domain filter can be readily used concurrently withpreviously known I/Q domain adaptive notch filters and spatial-nullingalgorithms by simultaneously optimizing filter weights in the I/Qdomain, amplitude domain, and spatial domain to realize enhancedperformance using an increased number of degrees of freedom, so as tomitigate an interference signal.

For example, as applied to suppression of interference in communicationor navigation systems, an adaptive temporal amplitude filter can be usedto notch out the frequency components of the interference that varydifferently than do the frequency components of the desired signal.Illustratively, based upon the amplitude of the interference signalbeing substantially constant, or slowly varying relative to the rate ofthe desired signal, the frequency spectrum of the interference amplitudecan appear to be narrow relative to that of the desired signal, even ifthe frequency spectra of the interference signal and the desired signalcompletely overlap in the I/Q domain. Alternatively, one or moreadaptive linear time domain filters can be used to mitigate interferencehaving an envelope that varies in time and produces non-zero frequencycomponents in the amplitude domain (non-constant envelope).

FIG. 3B illustrates steps in an exemplary method for reducing aninterference signal that spectrally overlaps a desired signal based on alinear time domain amplitude filter, according to some embodiments ofthe present invention. In some embodiments, method 300 can be used so asto process complex in-phase and quadrature samples of a baseband signalthat includes a desired signal and an interference signal thatspectrally overlaps the desired signal. Illustratively, method 300 caninclude obtaining amplitudes (and optionally also phases) of at least afirst subset of the complex in-phase and quadrature samples of thereceived baseband signal (step 301). For example, in some embodiments,interference suppression circuit 320 described above with reference toFIG. 3A can include envelope detector 322 configured to obtain theamplitudes, and optionally also the phases, of in-phase and quadraturesamples of the received baseband signal. In other embodiments, othercircuitry can be configured so as to obtain such amplitudes and phases.

Method 300 illustrated in FIG. 3B also includes applying a linear timedomain filter to the amplitudes so as to obtain processed amplitudes ofthe samples with reduced interference (step 302). For example, lineartime domain amplitude filter 323 can process the amplitudes of thesamples in a manner such as described above with reference to FIG. 3A soas to obtain processed amplitudes of the samples with reducedinterference. Method 300 illustrated in FIG. 3B further can includegenerating an output baseband signal with reduced interference based onthe phases and the processed amplitudes of the samples (step 303). Forexample, linear time domain amplitude filter 323 illustrated in FIG. 3Acan provide to optional signal construction circuit 325 or to signalconstruction circuit 130 illustrated in FIGS. 1A-1B the processedamplitudes, and envelope detector 322 such as provided in interferencesuppression circuit 320 of FIG. 3A or envelope detector 212 of thresholdcircuit 210 of FIG. 2A can provide to signal construction circuit 130 or325 the phases, based upon which signal construction circuit 130 or 325can generate an output baseband signal with reduced interference.

As noted above, in some embodiments, the linear time domain filterincludes a time domain notch filter. In some embodiments, the lineartime domain filter includes a plurality of time domain notch filters, atleast one of said time domain notch filters being centered at DC (e.g.,a high pass filter), at least one of said time domain notch filters notbeing centered at DC. In some embodiments, method 300 further includesadaptively adjusting said linear time domain filter so as to minimize aninterference to noise ratio (INR) or to maximize a carrier power tonoise spectral density ratio (C/No) or a signal to noise ratio (SNR),e.g., using any suitable combination of optional signal qualityestimator 324 and optional filter parameter adapter 326 illustrated inFIG. 3A.

FIG. 3C schematically illustrates exemplary circuit componentsconfigured to apply exemplary thresholds to an exemplary signal thatincludes an interference signal that spectrally overlaps a desiredsignal, according to some embodiments of the present invention. In theexemplary embodiment illustrated in FIG. 3C, two amplitude thresholdsare defined such that interference suppression is performed when theamplitude of a sample of the received signal is above a predeterminedfirst threshold and within a predetermined value relative to a priorestimate of the interference signal. Based upon both of such conditionsbeing satisfied, the interference signal is suppressed by an estimate ofthe amplitude of that interference signal within the sample. Based uponeither of such conditions not being satisfied, the sample is inhibitedfrom contributing to future amplitude estimates by gating the input toan estimation circuit (e.g., filter), and the value of the sampleamplitude is replaced by a constant value less than or equal to theaverage noise amplitude, in a manner similar to that described abovewith reference to FIGS. 2A-2E.

In the exemplary embodiment illustrated in FIG. 3C, an output amplituderesidual R_(o) is created by filtering the input amplitude signal “A”with at least a high pass notch filter. The filter may also includenotches at other frequencies, and may include a combination of severalfilters, and can have an arbitrary frequency response that includes atleast some rejection of the DC component. An (optionally delayed) inputamplitude signal A_(d) is produced from the input amplitude signal, “A”.An average of the input amplitude A, denoted here as “A_(e)” is obtainedfrom a separate circuit (e.g., amplitude averager 213 illustrated inFIG. 2A), not shown. This average amplitude is denoted A_(e) in figureFIG. 3C. A second input amplitude residual R_(i) is created bysubtracting an average of the input amplitude A_(e) from the inputamplitude A (e.g., using a circuit such as residual computation circuit215 describe above with reference to FIG. 2A). Based upon the inputamplitude A being less than a second threshold TH2, then that inputamplitude is blocked from entering the filter, and after an optionaldelay (corresponding to the optional delay of the signal A_(d), residualR_(o)), that input amplitude is passed to the output. In such a manner,TH2 can be set such that the interference is low enough such thatsuppression is not necessary for that input amplitude value. Based uponthe input amplitude residual being less than a first threshold TH1,then, the amplitude can be input into the filter and after an optionaldelay corresponding to the optional delay of the signal A_(d), residualR_(o) can be passed to the output Y for further processing. Based uponnone of these conditions are met, e.g., based upon R_(i) being largerthan (or equal to) TH1, the input amplitude which caused this largeresidual can be blocked from the averaging computation, and after anoptional delay, a constant is sent to the output Y. In FIG. 3, theconstant is zero for illustrative purposes; other values suitably can beused.

In an alternative implementation, the first and optional secondthresholds and integration period parameters can be adapted based on thecharacteristics of the measured signal and noise parameters in a manneranalogous to that described in U.S. Pat. No. 8,515,335, the entirecontents of which are incorporated by reference herein.

Signal processing based on linear time domain filters, such as providedherein, can be implemented using any suitable combination of hardwareand software, e.g., can be implemented as an appliqué, as a signalprocessing circuit, or as an algorithm in a suitably programmed radiofrequency receiver. For example, FIG. 3D schematically illustratesselected components of an exemplary appliqué implementation for reducingan interference signal that spectrally overlaps a desired signal basedon a linear time domain amplitude filter, according to some embodimentsof the present invention. In the embodiment of FIG. 3D, the signalprocessing is implemented as an appliqué in which a suitably programmedprocessor reduces the interference power to signal ratio (I/S). In theembodiment illustrated in FIG. 3D, an antenna receives a composite radiofrequency (RF) signal S(t) in which the desired signal S_(w)(t) iscorrupted by relatively strong interference S_(I)(t) and by noise n(t),S(t)=S_(w)(t)+S_(I)(t)+n(t). The composite signal S(t) is amplified by alow noise amplifier (LNA), then translated to an intermediate frequency(IF) using a downconverter where it is sampled by an analog-to-digitalconverter (ADC) and digitally converted to an in-phase (I) andquadrature (Q) baseband signal inside of the digital processor. Theprocessor processes the in-phase and quadrature signals in a mannerusing a linear time domain filter in a manner such as described abovewith reference to FIGS. 3A-3B, so as to generate an output basebandsignal with reduced interference. The processed in-phase and quadraturebaseband signals then are converted back to an IF carrier, where theyare converted to analog signals using a digital-to-analog converter(DAC) and translated back to RF using an upconverter before they enteran RF receiver.

FIG. 3E schematically illustrates selected components of an alternativeexemplary appliqué implementation for reducing an interference signalthat spectrally overlaps a desired signal. In the illustrativeimplementation illustrated in FIG. 3E, the signals are converted to andfrom I/Q (baseband) in the RF domain. In that implementation, the I andQ signals are digitized using two ADCs (one for I and one for Q), thenprocessed directly by the processor without further translation. Afterpassing through the processor, the processed I and Q signals areconverted to the analog domain using two DACs. In both cases, theprocessor reduces the interference into the receiver. Note that theembodiments illustrated in FIGS. 3D and 3E suitably can be applied toany aspect of the present circuits and methods, e.g., time domainfiltering, power domain analysis, or multiple clusters. FIGS. 3D and 3Eillustrate two exemplary ways to implement one or more of suchtechniques in the form of an add-on appliqué to a receiver.

In some embodiments, the present circuits and methods can transform ahigh I/S ratio into a low I/S ratio after processing. In someembodiments, a processing device in the receiver can be used such that aDAC and upconversion step need not necessarily be used, and optionallycan be omitted, after digital processing. In such embodiments, thereceiver's ADC, LNA, and downconverter can be used. The processingdevice in the receiver can include the receiver's existing processor, oran additional processing device can be connected to a pre-existingreceiver processor.

In embodiments such as illustrated in FIGS. 3D and 3E, the processor caninclude any suitable processing device configured to implement one ormore steps of FIG. 3B. Illustratively, the processor can include adigital processor. Devices in the receiver capable of performing theactions of the processor include, but are not limited to, an FPGA, anASIC, a CPU, a GPU, or other similar digital processing device.Alternatively, digital processors such as illustrated in FIGS. 3D and 3Ecan be replaced with an analog processor.

FIG. 3F illustrates the spectrum of an example received spread spectrumsignal compared to that of the noise and matched spectral interference.The resultant frequency spectrum after high-pass filtering in theamplitude domain is shown also. Notice that the power of theinterference signal has been reduced. The example received signalincluded a matched spectral C/A code interferer chipped at 1.023Mchips/sec, with an I/S=60 dB. Note that the interference spectrum inthe I/Q domain completely overlaps the signal of interest. As such,application of a temporal notch filter in the I/Q domain can filter notonly the interference signal, but also the desired signal. FIG. 3Gillustrates the resultant frequency spectrum of the amplitude before andafter applying a linear time domain filter to the example signalillustrated in FIG. 3F, according to some embodiments of the presentinvention. In this example, the linear time domain filter included atime-domain high-pass Butterworth filter, which can be considered to beequivalent to a notch filter at zero frequency in the amplitude domain.The Butterworth filter's stopband attenuation was 80 dB, the passbandfrequency was 700 kHz, and the stop-band frequency was 5.8 kHz.Alternative linear time domain filters also can be used. The spectrumillustrated in FIG. 3G is related to the Fourier transform of theamplitude samples. From FIG. 3G, it can be understood that although theinterference signal completely overlaps the desired signal in the I/Qspectral domain, the interference signal is localized in the amplitudedomain. Additionally, from FIG. 3G, it can be understood that the filterreduces the large center peak due to the interference signal. A lineartime domain filter, e.g., a time domain high-pass Butterworth filter orother suitable filter, can be adapted so as to remove such interferencewhile reducing or inhibiting impact on the desired signal.

FIG. 3H illustrates a comparison of the C/No for interferencesuppression based on applying a linear time domain filter to the examplesignal illustrated in FIG. 3F, according to some embodiments of thepresent invention. In this example, the “high pass amplitude domainfilter” curve was prepared by applying the Butterworth filter describedabove with reference to FIG. 3G, and applying that Butterworth filter inthe amplitude domain with reference to FIG. 3B, and the “theoryunprotected” curve was prepared without attempting to suppressinterference. From FIG. 3H, it can be understood that applying a highpass filter in the time domain suppresses interference. As in known inthe art, C/No is a measure of the quality of the desired C/A codesignal. A high C/No ratio indicates good signal quality. As can be seenfrom FIG. 3H, at a J/S ratio of 60 dB, the unprotected receiver has lessthan 5 dB of C/No, while the receiver which has a time domain high passnotch implemented can achieve 20 dB of C/No, showing that theinterference has been suppressed without completely removing the desiredsignal.

Accordingly, it can be understood that the present linear time domainfilters provide an effective amplitude domain interference suppressiontechnique that can be readily integrated, for example, with existingadaptive antenna suppression systems so as to provide additional degreesof freedom for improved performance of modern mean-forming null-steeringantijam antenna systems, as well as other exemplary systems such asmentioned elsewhere herein.

Reducing Interference Based on Using a Non-Unity Power of the Amplitudeof the Signals

Some embodiments of the present invention can separate the desiredsignal from the interference signal in one or more alternate domains,some or all of which are a non-linear function of the signal amplitude.Illustratively, an amplitude domain processing technique can be usedtogether with a non-linear function domains so as to enhanceinterference suppression against a wider range of interference types.Additionally, or alternatively, processing can be performed in aplurality of domains, including any suitable combination of the polaramplitude domain, I/Q domain, and nonlinear amplitude domain, e.g., soas to mitigate a wide range of interference types. Non-linear amplitudedomains can be expressed as D(n)=A^(n), where A corresponds to amplitudeand n is a real number that is not equal to 1 or 0. As one nonlimitingexample in which n=2, interference suppression can be performed in thepower (A²) domain of the signals.

For example, as noted above with reference to FIGS. 1A-1B, interferencesuppression circuit 120 can be configured so as to receive a signal thatincludes a desired signal and an interference signal that spectrallyoverlaps the desired signal, and to reduce the contribution of theinterference signal using any suitable circuitry. For example, in someembodiments, interference suppression circuit 120 can be configured toreduce the interference signal based on using a non-unity power of theamplitude of the received signal, e.g., in a manner such as describedwith reference to FIGS. 4A-4L. Interference suppression circuit 120suitably can receive the signal from optional threshold circuit 110,from A/D converter 12, from antenna/analog conditioner 11 or any othersuitable source. Although interference suppression circuit 120 iscompatible with optional threshold circuit 110, note that optionalthreshold circuit 110 suitably can be omitted.

FIG. 4A schematically illustrates an exemplary interference suppressioncircuit for use in reducing an interference signal that spectrallyoverlaps a desired signal based on a non-unity power of the amplitude ofthe signals, according to some embodiments of the present invention. Inthe nonlimiting embodiment illustrated in FIG. 4A, circuit 420 includesnon-unity circuit 421 and interference suppressor 422. In someembodiments, non-unity circuit 421 can be coupled to optional thresholdcircuit 110 via a suitable pathway so as to receive amplitudes of thereceived signal from threshold circuit 110. In other embodiments,interference suppression circuit can include an amplitude circuit (notspecifically illustrated) configured to receive the signal from optionalthreshold circuit 110, from A/D converter 12, from antenna/analogconditioner 11, or from any other suitable source, and configured toobtain an amplitude of the received signal. Additionally, the amplitudecircuit optionally can be configured to obtain a phase of the receivedsignal. For example, in some embodiments, the received signal can be inrectangular coordinates, and the amplitude circuit can include anoptional rectangular to polar converter configured to obtain anamplitude and a phase of the received signal. The amplitude circuit canbe coupled so as to provide the amplitude to non-unity circuit 421, and,in embodiments in which the phase also is obtained, optionally can becoupled so as to provide the phase to signal construction circuit 130illustrated in FIGS. 1A-1B. In one nonlimiting embodiment, the receivedsignal is a digitized baseband signal, and the amplitude circuit isconfigured to obtain amplitudes and phases of the complex in-phase andquadrature samples of the received baseband signal.

Non-unity circuit 421 illustrated in FIG. 4A can be configured to obtaina first non-unity power of amplitude of the received signal, andoptionally also to obtain a phase of the received signal; alternatively,the phase of the received signal can be obtained by another circuit suchas mentioned elsewhere herein. Illustratively, the non-unity power towhich A is raised can be ½, 2, ⅓, 3, or more than 3, or any othersuitable value that is not equal to 1. In some embodiments, theparticular non-unity power can be based upon the interference signaltype received. For example, some interference signal types may be moreseparable from the desired signal by using a given non-unity powerdomain than they are by using a unity power domain, or by using adifferent particular non-unity power. FIG. 4C is a plot of the frequencyspectra of components of an exemplary received signal, according to onenonlimiting example of the present invention. More specifically, FIG. 4Cshows the spectrum of a desired C/A code signal with the spectrum of aninterference signal which is a BPSK signal with a 1.023 MHz symbol ratewhich has been further AM modulated with 0.9 MHz sine wave. As is knownin the art, multiplying the BPSK signal by a 0.9 MHz sine wave producestwo “subcarriers” at +/−0.9 MHz, as can be seen in the interferencesignal of FIG. 4C. The amplitude spectrum and power spectrum frequencycontent of both the amplitude and the squared amplitude of thisAM-modulated BPSK signal is shown in FIG. 4D, which is a plot of thefrequency spectra of the amplitude and the power for the exemplaryreceived signal of FIG. 4C. The spectrum of the amplitude in FIG. 4Dshows peaks at multiple frequencies spaced every 2*0.9 MHz that foldback at the Nyquist frequency. Interference suppression could beperformed on this amplitude signal by notching every peak seen in theFFT of the amplitude, however, it could also be performed by notchingevery peak seen in the FFT of the square of the amplitude. The FFT ofthe square of the amplitude of this exemplary AM-modulated BPSKinterferer is also shown in FIG. 4D, and it is clear that there arefewer peaks to excise/notch in the squared amplitude spectrum ascompared to the amplitude spectrum. Accordingly, less of the desiredsignal can be removed when removing the interference signal whenexcising peaks in the FFT of the squared amplitude, as compared toexcising peaks in the FFT of the amplitude. The non-unity power can bechosen based upon the interference signal type, so as to reduce or tominimize the loss incurred when excising the interference. In oneexample, non-unity circuit 421 illustrated in FIG. 4A can be configuredto obtain the first non-unity power of the amplitude directly based uponin-phase and quadrature components of the received signal. As anotherexample, non-unity circuit 421 can be configured to obtain the firstnon-unity power of the amplitude based on determining an amplitude basedupon in-phase and quadrature components of the received signal, and thentaking that amplitude to a first non-unity power. Exemplary hardwareimplementations of non-unity circuit 421 include circuits that usemultipliers configured so as to multiply the amplitude by itself, toachieve a non-unity power of 2 for example.

In the embodiment illustrated in FIG. 4A, interference suppressioncircuit 420 also includes an interference suppressor 422 configured toapply an interference suppression algorithm to the non-unity power ofthe amplitude to output a processed amplitude with reduced contributionfrom the interference signal. Interference suppressor 422 can be coupledto non-unity circuit 421 via any suitable pathway so as to receive thefirst non-unity power of the amplitude therefrom. In some embodiments,the interference suppression algorithm includes one or more of frequencydomain excision, time domain filtering, and wavelet excision.Illustratively, the time domain filtering can include application of atime domain notch filter at DC (e.g., a high pass filter) or a timedomain notch filter with multiple notches. The interference can also besuppressed in the frequency domain of the non-unity power signal. Forexample, the FFT of the non-unity power signal can be computed, andfrequency domain excision performed. Exemplary hardware implementationsof interference suppressor include circuits that perform FFT excision.FFT excision, as is known in the art, includes performing an FFT,finding the largest peaks in the resulting frequency domain signal,setting those FFT bins to zero or some constant value, and subsequentlyperforming an IFFT of the signal. For illustrative purposes, based uponnon unity circuit 421 being configured to raise the amplitude to a powerof 2, then, following the IFFT, another circuit (not specificallyillustrated) would take the square root of the resulting IFFT signal toreturn back to the amplitude domain.

In some embodiments, interference suppression circuit 420 illustrated inFIG. 4A is coupled to a signal construction circuit configured togenerate an output signal with reduced contribution from theinterference signal interference based on a phase and the processedamplitude. For example, signal construction circuit 130 illustrated inFIGS. 1A-1B can be coupled to interference suppressor 422 so as toreceive therefrom a processed amplitude with reduced interference, andcan be coupled to an amplitude circuit (e.g., amplitude circuit(s) 211such as described above with reference to FIG. 2A, or an amplitudecircuit of interference suppression circuit 420, not specificallyillustrated) so as to receive therefrom phases of those samples, and canbe configured to generate an output signal based thereon.

Optionally, interference suppressor 422 illustrated in FIG. 4A furthercan be configured to apply interference suppression to the amplitude ofthe received signal, and to output the processed amplitude based on theinterference suppressed amplitude. For example, interference suppressor422 can include a linear time domain amplitude filter 323 such asdescribed above with reference to FIG. 3A, or can be configured toreduce the interference signal based on an estimate of the amplitude ofthe interference in the received signal, such as described above withreference to FIGS. 2A-2E.

As another option, non-unity circuit 421 optionally can be configured toobtain a second non-unity power of the amplitude, wherein the firstnon-unity power is different than the second non-unity power.Interference suppressor 422 further can be configured to applyinterference suppression to the second non-unity power of the amplitudeto output the processed amplitude based on the interference suppressedsecond non-unity power of the amplitude.

FIG. 4B illustrates steps in an exemplary method for reducing aninterference signal that spectrally overlaps a desired signal based on anon-unity power of the amplitude of the signals, according to someembodiments of the present invention. Method 400 illustrated in FIG. 4Bcan include obtaining a phase and a first non-unity power of amplitudeof the received signal (step 401). As noted above with reference to FIG.4A, non-unity circuit 421 can be configured to obtain a first non-unitypower of amplitude of the received signal, and optionally also to obtaina phase of the received signal; alternatively, the phase of the receivedsignal can be obtained by another circuit such as mentioned elsewhereherein. Illustratively, the non-unity power to which A is raised can be½, 2, ⅓, 3, or more than 3, or any other suitable value that is notequal to 1. Some signal types may be more separable from the desiredsignal when raised to a specific non-unity power, depending on thecharacteristics of the signal. Depending on the interference signaltype, a particular non-unity power may incur less signal loss whensuppression is performed in that domain versus a different non-unitypower. In one example, step 401 includes directly obtaining the firstnon-unity power of the amplitude based upon in-phase and quadraturecomponents of the received signal. In another example, step 401 includesobtaining the first non-unity power of the amplitude by determining anamplitude based upon in-phase and quadrature components of the receivedsignal, and then taking that amplitude to a first non-unity power.

Method 400 illustrated in FIG. 4B further can include inputting thefirst non-unity power of the amplitude into an interference suppressionalgorithm to output a processed amplitude with reduced contribution fromthe interference signal (step 402). Exemplary interference suppressionalgorithms that can be applied at step 402 include one or more offrequency domain excision, time domain filtering, wavelet excision, timedomain frequency excision, and subtracting an estimated amplitude of theinterference signal. Illustratively, the time domain filtering caninclude applying a time domain notch filter at DC (i.e., a high passfilter).

Method 400 illustrated in FIG. 4B also can include generating an outputsignal with reduced contribution from the interference signal based onthe phase and the processed amplitude. For example, signal constructioncircuit 130 illustrated in FIGS. 1A-1B can be coupled to interferencesuppressor 422 illustrated in FIG. 4A so as to receive therefrom aprocessed amplitude with reduced interference, and can be coupled to anamplitude circuit (e.g., amplitude circuit(s) 211 such as describedabove with reference to FIG. 2A, or an amplitude circuit of interferencesuppression circuit 420, not specifically illustrated) so as to receivetherefrom phases of those samples, and can be configured to generate anoutput signal based thereon.

Optionally, method 400 illustrated in FIG. 4B further can includeapplying interference suppression to the amplitude of the receivedsignal, wherein the processed amplitude is based on the interferencesuppressed amplitude. For example, interference suppressor 422illustrated in FIG. 4A can include a linear time domain amplitude filter323 such as described above with reference to FIG. 3A, or can beconfigured to reduce the interference signal based on an estimate of theamplitude of the interference in the received signal, such as describedabove with reference to FIGS. 2A-2E.

As another option, method 400 illustrated in FIG. 4B can includeobtaining a second non-unity power of the amplitude, wherein the firstnon-unity power is different than the second non-unity power, andapplying interference suppression to the second non-unity power of theamplitude, wherein the processed amplitude is based on the interferencesuppressed second non-unity power of the amplitude. For example,interference suppressor 422 illustrated in FIG. 4A can be configured toapply interference suppression to the second non-unity power of theamplitude to output the processed amplitude based on the interferencesuppressed second non-unity power of the amplitude.

As noted above, non-linear amplitude domains can be expressed asD(n)=A^(n), where A corresponds to amplitude and n is a real number thatis not equal to 1 or 0. As one nonlimiting example in which n=2,interference suppression can be performed in the power (A²) domain ofthe signals. For example, FIG. 4C is a plot of the spectrum of anexemplary received signal including a desired signal and an interferencesignal that spectrally overlaps the desired signal. The exemplaryreceived signal illustrated in FIG. 4C includes a 0.9 MHz spectrallyoverlapping AM modulated BPSK interferer that is 60 dB stronger than thedesired signal.

Illustratively, FIG. 4D is a plot of the frequency spectra of theamplitude and the power for the exemplary received signal of FIG. 4C. Itcan be understood from FIG. 4D that the interference signal is localizedto a single frequency in the domain of A², corresponding to twice the AMrate. As a result, the power (A²) domain substantially does not includealiased harmonics, and the interference can be suppressed withoutremoving the desired signal in a manner such as provided herein. Incomparison, the amplitude domain (A) domain includes a significantnumber of harmonics and other frequency components that can inhibitinterference suppression.

In some embodiments of the present invention, suppression of theinterference signal within a received signal includes transforming thereceived signal from the domain of A to the domain of A² (or othersuitable non-linear amplitude domain), then applying a notch filter toremove one or more nonzero frequency components. Alternatively, theinput I/Q samples can be directly converted to the domain of A², afterwhich a notch filter can be applied in the domain of A². Anotheralternative would be to remove nonzero interference using a fast Fouriertransform (FFT), apply a threshold, and inverse FFT (iFFT) in the A² orother nonlinear domain. Alternatively, a discrete Fourier transform canbe used.

Any suitable combination of hardware and software can be used to reduceinterference based on a non-unity power (A^(n), n≠1) of the amplitude ofthe received signal. For example, FIG. 4E schematically illustratesselected components of an exemplary interference suppression circuit foruse in reducing an interference signal that spectrally overlaps adesired signal based on a non-unity power of the amplitude of thesignals, according to some embodiments of the present invention. In FIG.4E, a suitable circuit or software module obtains the phase θ andnon-linear power A^(n) of the amplitude A based on the in-phase andquadrature components of the received signal. The non-linear power A^(n)of the amplitude is provided to a suitable circuit or software modulethat is configured to perform interference suppression (signalprocessing) on the A^(n) domain of the received signal so as to reducethe interference signal. The processed signal in the A^(n) domain andthe phase θ then are provided to a suitable circuit or software modulethat is configured to construct a signal in the I/Q domain that hasreduced contribution from the interference signal, based on theprocessed signal in the A^(n) domain and the phase θ.

Note that the circuit illustrated in FIG. 4E can perform signalprocessing in the power domain (A²) or in any other suitable nonlinearamplitude domain, e.g., a non-linear amplitude domain in which theinterference can be separated from the desired signal. As one example,FIG. 4F schematically illustrates selected components of anotherexemplary interference suppression circuit for use in reducing aninterference signal that spectrally overlaps a desired signal based on anon-unity power of the amplitude of the signals, according to someembodiments of the present invention. In FIG. 4F, n=2, and signalprocessing is performed in the power domain of the received signal. Asnoted elsewhere herein, signal processing (interference suppression) inany other suitable domain for which n≠1 can be used, optionally incombination with signal processing in the amplitude domain for whichn=1.

For example, consider the received amplitude values for the k^(th)sample of the received signal, A_(k) ²=I_(k) ²+Q_(k) ². For convenience,p_(k)=A_(k) ² can correspond to the sampled power values of the receivedsignal. The phase θ_(k) of the k^(th) sample of the signal can beobtained based on:

$\begin{matrix}{\theta_{k} = {{\tan^{- 1}\left( \frac{Q_{k}}{I_{k}} \right)}.}} & (7)\end{matrix}$

For power domain (A²) based interference suppression, the FFT or DFT ofthe p_(k) samples can be obtained based on:

$\begin{matrix}{P_{k} = {\sum\limits_{k = 0}^{N - 1}\; {p_{k}^{\frac{{- {j2\pi}}\; {kn}}{N}}}}} & (8)\end{matrix}$

Note that a transform alternatively can be implemented using a cosinetransform, short time Fourier transform, or related time/frequencytransform in at least one non-linear amplitude domain. Additionally,although use of overlapping FFTs or windowing is not specificallydescribed herein, it should be understood that such techniques suitablycan be employed in the nonlinear amplitude domain processing providedherein.

The magnitude M_(K) of the k^(th) FFT value can be expressed as:

M _(K)=√{square root over (Re ²(P _(k))+Im ²(P _(k)))}  (9)

After the magnitude values are obtained, such values optionally can becompared to a threshold M_(TH), e.g., by applying:

M _(K) ≧M _(TH)?  (10)

In some embodiments, the threshold can be selected to be a predeterminedlevel above the interference free bins (for example, 10 times theaverage magnitude of such bins or can be determined by first measuringthe average magnitude of such bins in an interference free environment,and then scaling the threshold according to the ADC attenuationresulting from automatic gain control. As such, the threshold can beoptimally set as a function of the interference-to-signal power ratio.Another approach is to set the threshold based on the average of theouter bins, with the assumption that such bins are interference free,such as can be the case for matched spectral interference. As anotherapproach, the threshold can be scaled by the receiver's estimate of theinterference to noise ratio or interference to signal ratio.

In some embodiments, for each sample for which M_(K) is equal to orexceeds M_(TH), indicating the presence of interference, the value ofthe magnitude can be replaced by a constant M₀, where M₀≧0. For example,in some embodiments, all values of M_(K) that satisfy this condition canhave their real part set to the average noise floor and their imaginarypart set to zero. Alternatively, both real and imaginary parts can beset to constants, e.g., that maximize the signal to noise or C/No afterinterference suppression.

In some embodiments, for a multiple-domain implementation, e.g.,involving both power domain and amplitude domain signal processing,values of M_(K) that are within a predetermined distance from zerofrequency will not be thresholded. In other words, the values of P_(k)within a predetermined distance from zero frequency can be leftunaltered.

After such a step, which can be considered to be an excision, an iFFT oriDFT can be applied according to:

$\begin{matrix}{{\overset{\prime}{p}}_{k} = {\frac{1}{N}{\sum\limits_{k = 0}^{N - 1}\; {P_{k}^{\frac{{j2\pi}\; {kn}}{N}}}}}} & (11)\end{matrix}$

where the prime is intended to denote the excised value of power. Theresultant processed amplitude can be expressed as:

Á _(k)=√{square root over (|{acute over (p)} _(k)|)}  (12)

In some embodiments, the magnitude of {acute over (p)}_(k) can beobtained before applying the square root to recover the processedamplitude Á_(k). Optionally, the amplitude can be retained as a complexquantity for further processing at the expense of power loss.

After removing the interference signal, which can be rapidly varying, inthe power (A²) domain, the phase and the processed amplitude Á_(k) canbe converted back to the I/Q domain, e.g., using:

I _(k) +jQ _(k) =Á _(k) e ^(jθ) ^(k)   (13)

where θ_(k) is the original phase of the k^(th) sample beforeinterference suppression.

FIG. 4G illustrates steps in another exemplary method for reducing aninterference signal that spectrally overlaps a desired signal based on anon-unity power of the amplitude of the signals, according to someembodiments of the present invention. Method 40 illustrated in FIG. 4Gincludes converting I/Q samples of a received signal to amplitudesquared (A²) and phase (step 41). Method 40 also includes computing theFFT of the real valued power (A²) values (step 42), e.g., as describedabove with reference to Equation 8. Method 400 also includesthresholding nonzero frequency FFT magnitude values exceeding athreshold based on the interference to noise level (step 43) andadjusting thresholded bins to the average interference free bin level(step 44), e.g., as described above with reference to Equations 9 and10. Method 40 also includes computing the inverse FFT for the adjustedFFT bins (step 45), e.g., as described above with reference to Equation11. Method 40 also includes converting the adjusted A₂ samples toamplitude (A) samples (step 46), e.g., as described above with referenceto Equation 12. Method 40 optionally also includes multiple-domainsignal processing, e.g., excising remaining interference in theamplitude domain (step 47). Exemplary methods for suppressinginterference in the amplitude domain are provided elsewhere herein.Method 40 also includes converting the excised amplitude samples back toI/Q samples using original phase values (step 48), e.g., as describedabove with reference to Equation 13.

In an exemplary multiple-domain implementation such as illustrated inFIG. 4G, rapidly varying amplitude contributions from the interferencesignal can be removed in a nonlinear domain, such as the power domain,using FFT, thresholding, and inverse FFT such as illustrated in FIG. 4J.FIG. 4J illustrates steps in another exemplary method for reducing aninterference signal that spectrally overlaps a desired signal based on anon-unity power of the amplitude of the signals, according to someembodiments of the present invention. In FIG. 4J, N samples X₁, X₂, . .. X_(N) of a received signal having amplitudes A_(k) ^(n) are obtained(step 4001). The N samples are Fourier transformed to obtaincorresponding magnitudes M₁, M₂, . . . M_(N) (step 4002). For each ofthe magnitudes, if that magnitude M_(i) equals or exceeds a thresholdM_(th), the magnitude is set to M₀ (step 4003), e.g., such as describedabove with reference to Equation 12. The processed magnitudes areinversely Fourier transformed (step 4004) to obtain processed samplesX₁, X₂, . . . X_(N) having processed amplitudes A_(k)′^(n) (step 4005).In some embodiments, FFT bins near zero frequency (e.g., within apredetermined distance from zero frequency, such as described elsewhereherein) are not excised. Instead, the interference in such bins can beremoved using a subsequent step, e.g., amplitude domain processing suchas described with reference to FIG. 4H, or alternative nonlinear domainprocessing such as described with reference to FIG. 4I. Alternatively,substantially all interference can be removed in the power domain.

In power-domain signal processing such as illustrated in FIGS. 4G and4J, the signal can be converted to the amplitude domain and subsequentlyprocessed to remove interference contributions that have slowly varyingamplitudes. Note that a power-domain notch filter or other type offilter may also be used to selectively remove rapidly varyinginterference in the power domain. Alternatively, a short-term Fouriertransform or similar transform-domain excision approach also can be usedto separate interference from the desired signal in the power (A²)domain. Illustratively, the implementations of FIGS. 2 and 3C, theexemplary implementations described in U.S. patent application Ser. No.14/262,532, or any other suitable amplitude domain interferencesuppression algorithm, can be used to perform the amplitude domainsignal processing. Alternatively, a second FFT/iFFT such as described inHenttu can be applied in the amplitude domain.

FIG. 4H schematically illustrates selected components of anotherexemplary interference suppression circuit for use in reducing aninterference signal that spectrally overlaps a desired signal based on anon-unity power of the amplitude of the signals, according to someembodiments of the present invention. In FIG. 4H, a suitable circuit orsoftware module obtains the phase θ and non-linear power A^(n) of theamplitude A based on the in-phase and quadrature components of thereceived signal. The non-linear power A^(n) of the amplitude is providedto a suitable circuit or software module that is configured to performinterference suppression (signal processing) on the A² (power) domain ofthe received signal so as to reduce the interference signal. Theprocessed signal in the A² (power) domain and the phase θ then areprovided to a suitable circuit or software module that is configured totransform the processed signal back to the A (amplitude) domain, e.g.,by taking the square root of the output from the power domainprocessing. The amplitude A then is provided to a suitable circuit orsoftware module that is configured to perform signal processing(interference suppression) in the amplitude domain, such as providedelsewhere herein. The processed amplitude then is provided to a suitablecircuit or software module that is configured to construct a signal inthe I/Q domain that has reduced contribution from the interferencesignal, based on the processed signal in the A domain and the phase θ.

Note that the circuit illustrated in FIG. 4H can be configured so as toperform signal processing in the power domain (A²) or in any suitablenumber and combination of linear and non-linear amplitude domains, e.g.,a plurality of non-linear amplitude domains in which the interferencecan be separated from the desired signal. As one example, FIG. 4Ischematically illustrates selected components of another exemplaryinterference suppression circuit for use in reducing an interferencesignal that spectrally overlaps a desired signal based on multiplenon-unity powers of the amplitude of the signals, according to someembodiments of the present invention. In FIG. 4I, a suitable circuit orsoftware module obtains the phase θ and a first non-linear power A^(n)of the amplitude A based on the in-phase and quadrature components ofthe received signal. The non-linear power A^(n) of the amplitude isprovided to a suitable circuit or software module that is configured toperform interference suppression (signal processing) on the A^(n) domainof the received signal so as to reduce the interference signal. Theprocessed signal in the A^(n) domain and the phase θ then are providedto a suitable circuit or software module that is configured to transformthe processed signal to a second non-linear domain of power m (m≠n≠1≠0)e.g., by taking the m/n root of the output from the power domainprocessing. The A^(m) domain signal then is provided to a suitablecircuit or software module that is configured to perform signalprocessing (interference suppression) in the A^(m) domain, such asprovided elsewhere herein. The processed amplitude then is provided to asuitable circuit or software module that is configured to construct asignal in the I/Q domain that has reduced contribution from theinterference signal, based on converting the processed signal in theA^(m) domain back to the A domain, and the phase θ. Signal processing(interference suppression) in any other suitable domain for which m≠n≠1can be used, optionally in combination with signal processing in theamplitude domain for which n=1. Note that m and n can be independentlyselected integers or fractions.

Note that thresholds M_(TH), M_(th) such as described herein can be setso that the interference is detected above the noise level. For example,the threshold can be set by measuring the power of the interference-freeFFT bins and setting the threshold to be a multiple of theinterference-free bin power. Other approaches known in the art can beused to set the FFT threshold M_(th). In one example, the threshold canbe set to be equal to the average magnitude in dB plus a constant αselected as a function of the ISR, INR, or some other suitable quantity,as follows:

$\begin{matrix}{M_{th} = {{\frac{1}{N_{FFT}}{\sum\limits_{k = 1}^{N_{FFT}}\; {10*{\log_{10}\left( Z_{k} \right)}}}} + \alpha}} & (14)\end{matrix}$

Alternatively, this can be used as an initial threshold and iterativelychanged so as to optimize, for example, received signal to noise ratioor C/No. The threshold also may be determined before the interference isdetected, by measuring the average FFT bin magnitude in the A² domaindue to the signal and noise contributions and setting the threshold tobe, for example, 10 dB above this level. In another example, thethreshold can be based on the measured interference to noise level,e.g., as determined by an ADC.

FIG. 4K is a plot of the frequency spectra of the amplitude and thepower for the exemplary received signal of FIG. 4C after interferencesuppression using the method of FIG. 4G, according to some embodimentsof the present invention. After applying both power-domain andamplitude-domain signal processing, note that the frequency componentsnear zero frequency in the power domain have been retained.Subsequently, the amplitude domain processing of FIG. 2E was used toremove low frequency amplitude spectral components including remainingnear constant amplitude components of the interference signal. In otherwords, the AM modulation of the PRN code interferer was removed in thepower domain, with the nearly constant envelope portion of theinterferer removed in the amplitude domain according to an exemplarymultiple-domain implementation.

FIG. 4L illustrates a comparison of the C/No for interferencesuppression based on applying multiple domain interference suppressionusing the method of FIG. 4G to the example signal illustrated in FIG. 4Caccording to some embodiments of the present invention. Morespecifically, FIG. 4L illustrates the results of a simulation for the0.9 MHz AM modulated BPSK interference signal as a function ofinterference to signal ratio for the case of a 1.023 MCPS C/A codesignal. While results are shown for a C/A code signal received by a GPSreceiver, it should be understood that non-linear domain processing, andmultiple-domain processing, suitably can be applied to any signalreceiver of interest, including other GNSS signal receivers, wirelesssystem receivers, Bluetooth receivers, WiFi receivers, satellitecommunication receivers, radar system receivers, and the like.

Note that while the examples provided with reference to FIGS. 4K-4Lillustrate a multiple-domain approach, using amplitude-squared andamplitude excision using an amplitude estimation approach, in otherembodiments the interference signal can be reduced strictly in the A²domain by applying an FFT, setting to zero all bins that exceed athreshold, and transforming back to the amplitude domain beforetransforming to the I/Q domain. Alternative amplitude-domain approachesalso can be used such as the approach of FIG. 3C or by performingFFT-based excision in the nonlinear amplitude domain or in the linearpolar amplitude domain. As noted above with reference to FIG. 4I, anysuitable number of linear and non-linear amplitude domains can be usedfor interference suppression. Additionally, any suitable number oflinear and non-linear amplitude domains can be combined with previouslyknown I/Q domain processing, such as narrow-band excision processing.

Reducing Interference Based on Clustering the Amplitudes of the Signals

In some embodiments, single or multiple broadband interference signal(s)that spectrally overlap a desired signal can be suppressed based onclustering amplitudes of the signals. For example, rather than having aconstant envelope, the interference signal(s) can have multiple discreteamplitude levels over a given time period that potentially can make itdifficult to suppress the interference. As provided herein, clusteringamplitudes of the received signal can be used so as to identify andsuppress the interference. In some embodiments, the present circuits andmethods convert digitized in-phase (I) and quadrature (Q) samples of areceived signal, which includes a desired signal and an interferencesignal that overlaps the desired signal, to amplitude and phase samples.The present circuits and methods can identify one or more clusters ofamplitude samples with a similar amplitude as one another, can estimatethe amplitude of each cluster over time, can assign each amplitudesample to an appropriate (e.g., nearest) cluster, and, when indicated bya decision circuit, can perform interference suppression on the assignedamplitude sample. Illustratively, an appropriate amplitude can besubtracted from the assigned amplitude sample. The residual amplitude ofthe signal can be combined with the unaltered phase samples, to generatean output in the I and Q signal domain. The net effect can be thesuppression of many kinds of interference signals in which the amplitudeof the interference signal(s) can vary significantly over time.

For example, as noted above with reference to FIGS. 1A-1B, interferencesuppression circuit 120 can be configured so as to receive a signal thatincludes a desired signal and an interference signal that spectrallyoverlaps the desired signal, and to reduce the contribution of theinterference signal using any suitable circuitry. For example, in someembodiments, interference suppression circuit 120 can be configured toreduce the interference signal based on clustering the amplitudes of thesignals, e.g., in a manner such as described with reference to FIGS.5A-5Q. Interference suppression circuit 120 suitably can receive thesignal from optional threshold circuit 110, from A/D converter 12, fromantenna/analog conditioner 11 or any other suitable source. Althoughinterference suppression circuit 120 is compatible with optionalthreshold circuit 110, note that threshold circuit 110 suitably can beomitted.

FIG. 5A schematically illustrates an exemplary interference suppressioncircuit for use in reducing an interference signal that spectrallyoverlaps a desired signal based on clustering the amplitudes of thesignals, according to some embodiments of the present invention. In thenon-limiting embodiment illustrated in FIG. 5A, circuit 520 includescluster definition circuit 521, cluster assignment circuit 522, andinterference suppressor 523. In some embodiments, cluster definitioncircuit 521 can be coupled to optional threshold circuit 110 via asuitable pathway so as to receive amplitudes of samples of the receivedsignal from threshold circuit 110. In other embodiments, interferencesuppression circuit can include an amplitude circuit (envelopeestimator, not specifically illustrated) configured to receive samplesof the amplitude (also referred to as amplitude samples) of the signalfrom optional threshold circuit 110, from A/D converter 12, fromantenna/analog conditioner 11, or from any other suitable source, andconfigured to obtain an amplitude of the received signal. Additionally,the amplitude circuit (envelope estimator) optionally can be configuredto obtain a phase of samples of the received signal (also referred to asphase samples). For example, in some embodiments, the received signalcan be in rectangular coordinates, and the amplitude circuit can includean optional rectangular to polar converter configured to obtain anamplitude and a phase of the received signal. The amplitude circuit canbe coupled so as to provide the amplitude to cluster definition circuit521, and, in embodiments in which the phase also is obtained, optionallycan be coupled so as to provide the phase to signal construction circuit130 illustrated in FIGS. 1A-1B. In one nonlimiting embodiment, thereceived signal is a digitized baseband signal, and the amplitudecircuit is configured to obtain amplitudes and phases of the complexin-phase and quadrature samples of the received baseband signal.

Cluster definition circuit 521 illustrated in FIG. 5A can be configuredto define a plurality of clusters, each cluster of the plurality havinga corresponding cluster amplitude. Cluster definition circuit 521 can beconfigured to define, and optionally to update over time, the pluralityof clusters in any suitable manner such as described in greater detailbelow. As one example, FIG. 5C illustrates an example amplitude(magnitude of I+jQ) for the sum of 4 randomly phased BPSK interferencesignals. Notice that in this example, 8 amplitude levels are clearlypresent for 4 interference signals. In some embodiments, clusterdefinition circuit 521 can be configured to define a plurality ofclusters based upon a distribution of amplitudes that are present in thereceived signal. Using the example illustrated in FIG. 5C, clusterdefinition circuit 521 can be configured to define 8 clusters, eachcorresponding to an amplitude level present in the received signal.Other exemplary methods and circuits for defining clusters are providedfurther below.

Interference suppression circuit 520 illustrated in FIG. 5A alsoincludes cluster assignment circuit 522. Cluster assignment circuit 522can be configured so as to receive via a suitable pathway the clusterdefinitions defined by cluster definition circuit 521, and also so as toreceive via a suitable pathway the sample amplitudes from the amplitudecircuit (not specifically illustrated in FIG. 5A). Cluster assignmentcircuit 522 can be configured to assign each sample of a subset of thesamples to one of the clusters based on the amplitude of that sample andbased on one or more of the cluster amplitudes. As one nonlimitingexample, cluster assignment circuit 522 can be configured to compare theamplitude of each sample of a subset of the samples to one or more ofthe clusters, and to assign each sample to the respective closest one ofthe clusters. Using the example illustrated in FIG. 5C, clusterassignment circuit 522 can be configured to compare the amplitude ofeach sample of the subset to the 8 clusters defined by clusterdefinition circuit 521, and to assign each sample to the closest one ofthose 8 clusters for that sample. Note, however that cluster assignmentcircuit 522 optionally can be configured so as not to assign certainsamples to a cluster. For example, based upon the amplitude of thesample exceeding a threshold, then cluster assignment circuit 522 can beconfigured to discard the sample or to set the amplitude for that valueto zero or other constant. Or, for example, based upon the amplitude ofthe sample exceeding a threshold, then cluster assignment circuit 522can be configured to send an appropriate signal to interferencesuppression circuit 520 that the sample has an amplitude exceeding thethreshold, and interference suppression circuit 520 can be configured todiscard the sample or to set the amplitude for that value to zero orother constant.

Interference suppression circuit 520 illustrated in FIG. 5A furtherincludes interference suppressor 523 configured to receive via asuitable pathway the cluster definitions defined by cluster definitioncircuit 521, so as to receive via a suitable pathway the sampleamplitudes from the amplitude circuit (not specifically illustrated inFIG. 5A), and to receive via a suitable pathway the cluster assignmentsfrom cluster assignment circuit 522. Interference suppressor 523 can beconfigured to suppress interference to each sample of the first subsetof the samples based on the amplitude of that sample and based on thecluster amplitude of the cluster to which that sample is assigned so asto obtain a processed amplitude of that sample with reducedinterference. As one example, interference suppressor 523 can beconfigured to subtract the amplitude of that sample from the clusteramplitude of the cluster to which that sample is assigned, or to applyany other suitable interference suppression algorithm to that sample.For example, interference suppressor 523 can be configured to transformthat sample into a transform domain representation, excise at least aportion of the interference in the transform domain, and perform aninverse transform to obtain the processed amplitude of that sample. Thetransform can be a Fourier transform, a wavelet transform, or any othersuitable transform.

Interference suppressor 523 optionally can be configured so as tosuppress interference in only a subset of the samples that it receivesfrom cluster assignment circuit 522. For example, interferencesuppressor 523 can be configured to determine that contribution ofinterference need not be suppressed for at least one sample of a secondsubset of the samples, based on the cluster to which that sample'samplitude is assigned. Illustratively, interference suppressor 523optionally can be configured, based upon the amplitude of at least oneof the samples of the second subset and a first threshold, to output theamplitude of that sample as the processed amplitude of that sample. Or,as mentioned above, interference suppressor 523 can be configured todetermine, e.g., based on the cluster to which the sample's amplitude isassigned or other suitable signal from cluster assignment circuit 522,that interference is sufficiently high for that sample that the sampleamplitude should be modified or discarded. For example, interferencesuppressor 523 can be configured, based upon the amplitude of at leastone of the samples of the second subset and a second threshold, to apredetermined value as the processed amplitude of that sample.

In some embodiments, interference suppression circuit 520 illustrated inFIG. 5A is coupled to a signal construction circuit configured togenerate an output signal with reduced contribution from theinterference signal interference based on a phase and the processedamplitude. For example, signal construction circuit 130 illustrated inFIGS. 1A-1B can be coupled to interference suppressor 523 so as toreceive therefrom a processed amplitude with reduced interference, andcan be coupled to an amplitude circuit (e.g., amplitude circuit(s) 211such as described above with reference to FIG. 2A, or an amplitudecircuit (envelope estimator) of interference suppression circuit 520,not specifically illustrated) so as to receive therefrom phases of thosesamples, and can be configured to generate an output signal basedthereon.

Note that in some circumstances, one or more characteristics (such asamplitude levels present) of the interference signal or the desiredsignal, or both, can remain substantially constant over time. In othercircumstances, one or more characteristics (such as amplitude levelspresent) of the interference signal or the desired signal, or both, canvary over time. In such circumstances, it can be useful for interferencesuppression circuit 520 illustrated in FIG. 5A to be configured so as toprovide flexibility in the definition of clusters, and assignment ofamplitudes to clusters, over time. In some embodiments, clusterdefinition circuit 521 can be configured to estimate each clusteramplitude over a period of time. Cluster definition circuit 521 can beconfigured to estimate cluster amplitudes in any suitable manner. Forexample, cluster definition circuit 521 optionally can be configured toestimate the cluster amplitude of each cluster based on averaging, overthe period of time, the amplitudes of the samples assigned to thatcluster. Such averaging can be performed using any suitable circuitry.For example, cluster definition circuit 521 can include a finite impulseresponse (FIR) or infinite impulse response (IIR) type digital filterconfigured to perform such averaging. In some embodiments, the FIR orIIR type digital filter can be configured to receive as input only theamplitudes of the samples assigned to the corresponding cluster, and toupdate an output of the filter based only upon a sample having a newamplitude being assigned to the corresponding cluster. For example,based upon the levels of amplitude samples assigned to a clusterincreasing or decreasing over time, cluster definition circuit 521(e.g., an FIR or IIR type digital filter of cluster definition circuit521) can be configured to modify the definition of that cluster. In amanner analogous to that described above, interference suppressor 523can be configured to subtract the amplitude of that sample from theestimated cluster amplitude of the cluster to which that sample isassigned. In embodiments in which cluster definition circuit 521includes an FIR or IIR type digital filter, interference suppressor 523also can be configured to compensate for the group delay of the FIR orIIR type filter prior to performing the subtraction.

For example, FIG. 5P schematically illustrates selected components of anexemplary circuit which shows one possible FIR implementation ofinterference suppressor 523. For this exemplary circuit, there are twoclusters shown. Each cluster averages incoming samples with a recursiverunning sum, a structure well known in the art, which includes a delayline followed by an integrator. The output of the recursive running sumis divided by D, the number of taps in the delay line, so as to producea moving average of the input sample amplitudes. The cluster assignmentcircuit 522 produces cluster pointers which direct the incoming sampleinto of one of two cluster averaging circuits. In this exemplary circuitthere are only 2 clusters, however there could be any suitable number ofclusters. The cluster pointer and the incoming sample are delayed tocompensate for the group delay of the recursive running sum averager. Inthis example, the group delay of the recursive running sum is D and thecompensating delay is D/2, however any compensating delay can be chosen,including no delay. The delayed cluster pointer chooses which of twocluster averager outputs to choose, and the delayed input amplitudesample is subtracted from the corresponding cluster average to producean amplitude residual.

It will be clear to those skilled in the art that the subtractionperformed in FIG. 5P can be configured to subtract the average clusteramplitude from the amplitude sample, or can be configured to subtractthe amplitude sample from the average cluster amplitude. Bothconfigurations can provide an amplitude residual which can be used infurther processing to suppress the interference and recover the desiredsignal.

Interference suppression circuit 520 illustrated in FIG. 5A can includea random access memory (RAM) (not specifically illustrated) configuredso as to store, and optionally to update over time, cluster definitionsobtained by cluster definition circuit 521. For example, in embodimentsin which cluster definition circuit 521 includes an IIR type filter,cluster definition circuit 521 can be configured to generate an outputof the filter using steps that include storing the cluster average intoa RAM at an address corresponding to the cluster. Optionally, clusterdefinition circuit 521 also can be configured to update the respectivecluster average every sample by reading a value of the average from theRAM. In some embodiments, cluster definition circuit 521 further can beconfigured to multiply the read value of the average by a coefficient,to add the multiplied coefficient to a multiplied version of theamplitude of that sample to produce the filter output, and to re-writethe new cluster average back into RAM at the address corresponding tothe cluster. In one non-limiting embodiment, a single IIR filter isbeing implemented by the RAM, multipliers, and adder. Each clusteraverage is stored in memory and the need for dedicated multipliers andadders for each cluster IIR filter is obviated, e.g., the multiplierscan be time-shared amongst the clusters to reduce hardware complexity.An exemplary schematic of this implementation is shown in FIG. 5Q, wherethe output of a RAM is multiplied by a coefficient B and added to amultiplied version of an input amplitude sample. The output of thisaddition is stored back in RAM at the address designated for thatparticular cluster. Thus the RAM stores the cluster averages for all theclusters, and several IIR filters are implemented while only using up 2multipliers and a single adder unit. As another example, in embodimentsin which cluster definition circuit 521 includes an FIR moving averagefilter, the FIR moving average filter can be configured to implement arecursive running sum.

It should be understood that such circuitry for defining and updatingcluster definitions is merely exemplary, and that cluster definitioncircuit 521 can be configured so as to define or update a cluster in anysuitable manner. For example, in some embodiments, cluster definitioncircuit 521 can be configured to define the clusters at a first timebased on a histogram of the amplitudes of the samples of the receivedsignal at the first time, in a manner such as described further below.Optionally, cluster definition circuit 521 can be configured tore-define the clusters at a second time based on a histogram of theamplitudes of the samples of the received signal at the second time. Asanother example, in some embodiments, cluster definition circuit can beconfigured to create or destroy at least one cluster or merging at leasttwo clusters according to a set of rules. Illustratively, clusterdefinition circuit 521 can be configured to measure respectiveintra-cluster distances between pairs of clusters based on the clusteramplitudes of those clusters. The set of rules, which can be stored inRAM or can be implemented in hardware, can be defined such that basedupon any two clusters having an intra-cluster distance that is less thana threshold, those two clusters are to be merged. In some embodiments,cluster definition circuit 521 can be configured to merge two clustersby, for example, averaging the cluster amplitudes of those two clusters,deleting one of the two clusters, and assigning the average of thecluster amplitudes of those two clusters to the other of the two bins.Optionally, cluster definition circuit 521 also can be configured tomeasure a minimum distance between the amplitude of at least one of thesamples and at least a subset of the cluster amplitudes. The set ofrules can define that based upon the smallest minimum distance betweenthat amplitude and any of the cluster amplitudes of the subset exceedinga threshold, a new cluster having a cluster amplitude equal to theamplitude for that sample is to be added. In still other embodiments,cluster definition circuit 521 can be configured to define the pluralityof clusters based on partitioning an available digital amplitude spaceinto a plurality of bins. The bins can be spaced approximately evenlyacross the available amplitude space, or can be spaced unevenly acrossthe available amplitude space. Cluster definition circuit 521 optionallycan be configured to update the number of bins and locations of binsbased upon one or more properties of the received signal.

Additionally, it should be understood that cluster assignment circuit522 can be configured to assign an amplitude sample to one of theclusters defined by cluster definition circuit 521 using any suitabletechnique. As one nonlimiting example, cluster assignment circuit 522can be configured to assign each sample of the first subset of thesamples to one of the clusters based on a respective minimum distancebetween the amplitude of that sample and a plurality of the clusteramplitudes, and to assign the sample to the cluster for which theminimum distance is the smallest. Other techniques suitably can be used.

FIG. 5B illustrates steps in an exemplary method for reducing aninterference signal that spectrally overlaps a desired signal based onclustering the amplitudes of the signals, according to some embodimentsof the present invention. Method 500 illustrated in FIG. 5B can includeobtaining amplitudes (and optionally) phases of the samples of thereceived signal (501). For example, interference suppression circuit 520illustrated in FIG. 5A or interference reduction circuit 100 illustratedin FIGS. 1A-1B suitably can include an amplitude circuit (envelopeestimator) configured so as to obtain an amplitude (and optionally aphase) of each sample of the received signal. Method 500 illustrated inFIG. 5B also can include defining a plurality of clusters, each clusterof the plurality having a corresponding cluster amplitude (502). Forexample, interference suppression circuit 520 illustrated in FIG. 5A caninclude cluster definition circuit 521 configured so as to define aplurality of clusters, each cluster having a corresponding amplitude.Method 500 illustrated in FIG. 5B further can include assigning eachsample of a first subset of the samples to one of the clusters based onthe amplitude of that sample and based on one or more of the clusteramplitudes (503). For example, interference suppression circuit 520illustrated in FIG. 5A can be configured so as to assign each sample ofa first subset of the samples to one of the clusters based on theamplitude of that sample and based on one or more of the clusteramplitudes. Method 500 illustrated in FIG. 5B further can includesuppressing contribution of interference to each sample of the firstsubset of the samples based on the amplitude of that sample and based onthe cluster amplitude of the cluster to which that sample is assigned soas to obtain a processed amplitude of that sample with reducedinterference (504). For example, interference suppression circuit 520illustrated in FIG. 5A can include interference suppressor 523configured to suppress contribution of interference to each sample ofthe first subset of the samples based on the amplitude of that sampleand based on the cluster amplitude of the cluster to which that sampleis assigned so as to obtain a processed amplitude of that sample withreduced interference. Method 500 illustrated in FIG. 5B also can includegenerating an output signal with reduced interference based on thephases and the processed amplitudes of the samples of the first subsetof the samples (505). Any suitable combination of hardware and softwarein interference suppression circuit 520 illustrated in FIG. 5A andinterference reduction circuit 100 illustrated in FIGS. 1A-1B can beused so as to generate an output signal with reduced interference basedon the phases and the processed amplitudes of the samples of the firstsubset of the samples.

It should be understood that any suitable combination of hardware andsoftware can be used so as to implement interference suppression circuit520 illustrated in FIG. 5A or method 500 illustrated in FIG. 5B. As oneexample, any suitable circuits of interference suppression circuit 520can be implemented using a suitably programmed microprocessor (which canbe coupled to RAM storing instructions for implementing some or allsteps of method 500), or an FPGA or graphics processing unit configuredso as to implement some or all steps of method 500. Additionally, itshould be understood that interference suppression circuit 520illustrated in FIG. 5A or method 500 illustrated in FIG. 5B can suppressinterference in any suitable type of received signal, including receivedsignals that include one or more interference signals that includenearly constant envelopes, are based on quadrature amplitude shiftkeying (QAM), are based on amplitude shift keying (ASK), are based onBPSK, or any other multi-level interference signal or combination ofsingle-level or multi-level interference signals.

FIG. 5D schematically illustrates selected components of an exemplaryinterference suppression circuit for use in reducing an interferencesignal that spectrally overlaps a desired signal based on based onclustering the amplitudes of the signals, according to some embodimentsof the present invention. In FIG. 5D, a suitable circuit or softwaremodule obtains the phase θ_(k) and amplitude A_(k) of k samples based onthe in-phase and quadrature components of the received signal. Theamplitudes A_(k) of the samples of the received are provided to asuitable circuit or software module configured as a multi-levelamplitude cluster estimator that is configured to estimate some numberof amplitude levels over a period of time, e.g., using N digitalfilters, so as to define a plurality of amplitude clusters A_(k) ¹,A_(k) ², A_(k) ³ . . . A_(k) ^(N). A suitable circuit or software modulecompares the amplitude of each incoming sample to one or more of theamplitude clusters, and assigns that amplitude to one of the clustersA_(k) ¹, e.g., assigns that amplitude to the cluster with the amplitudethat is closest to the sample's amplitude. A suitable decision circuitor software module applies a criterion such as whether or not theinterference to noise level for that sample is above a predefined level(e.g., resulting in the “True” condition illustrated in FIG. 5D), orwhether interference need not be suppressed in the sample (e.g.,resulting in the “False” condition illustrated in FIG. 5D). For samplesfor which the decision circuit or software module determined a “True”condition, a suitable circuit or software module then subtracts thesample's amplitude from the amplitude of the cluster to which it wasassigned. In an alternative implementation (not specifically illustratedin FIG. 5D), the decision circuit or software module also can choose toset the amplitude of a sample to zero or to a predefined value (whichcan be referred to “blanking” the sample) based upon that sample'samplitude being too far away from any of the amplitude clusters. Theprocessed amplitude A_(k)′ resulting from the subtraction and the phaseθ then are provided to a suitable circuit or software module that isconfigured to construct a signal in the I/Q domain that has reducedcontribution from the interference signal.

In an actual hardware or software implementation, the circuitillustrated in FIG. 5D optionally can be modified so as to include delaylines on one or both of the phase samples and the amplitude samples. Thephase samples can be delayed before being converted back to the I/Qdomain, so as to match the overall circuit processing time. Also,because the multi-level amplitude cluster estimator can take a fixedamount of time to determine the estimation (cluster) value, this delaycan be accounted for in both the decision circuit and the subtraction.Amplitude samples can be inserted into a delay line prior to thesummation illustrated in FIG. 5D so that the delay matches that of theestimator processing time. Additionally, the amplitude samples insertedinto the “False” branch of the decision circuit also can have some delaythat matches the time necessary to compute a decision.

Additionally, note that interference suppression circuit 520 illustratedin FIG. 5B or the circuit illustrated in FIG. 5D suitably can beconfigured so as to implement any suitable combination of steps forsuppressing interference in a received signal. In one example, such acombination of steps includes some or all of the following:

1. Sample a received analog signal with an analog converter. Convertsignal samples into amplitude samples and retain phase values for eachsignal sample.

2. Identify cluster(s) of amplitude samples with a similar amplitude anddetermine an initial value for each cluster.

3. Compute current output of N amplitude level estimators, or amplitudeclusters using a time domain filter (e.g., FIR, IIR).

4. Optionally adapt the number of amplitude clusters N, based on theirinter-cluster distance (or other suitable metric).

5. Subtract the amplitude level of the cluster that is closest to thecurrent amplitude sample from the current amplitude sample wheneverdirected to by a decision circuit or application of a rule.

6. Convert the residual after subtraction to an I/Q signal value usingthe phase corresponding to the amplitude sample before subtraction.

7. I/Q samples can be processed normally by a digital receiver oroptionally converted to the analog domain for an appliquéimplementation.

8. Optionally re-initialize the amplitude clusters.

9. Repeat steps 3-8.

Additionally, note that interference suppression circuit 520 illustratedin FIG. 5B or the circuit illustrated in FIG. 5D suitably can beconfigured so as apply any suitable time-domain or frequency-domainprocessing in one or more amplitude or non-linear amplitude domains soas to separate non-constant interference from a desired signal in areceiver. The in-phase and quadrature components of the received signalcan be transformed to an amplitude domain A, or to a domain based on anonlinear function of the amplitude A^(m) where m≠1, in a manneranalogous to that described above with reference to FIGS. 4A-4L.

Consider the case of amplitude-domain processing first. Lets(t)=Re(Ae^(jθ)e^(jωt))=I cos(ωt)−Q sin(ωt). I is the in-phase componentof the signal and Q is the quadrature component of the signal. Theamplitude can be computed from these components as can be expressed by:

A(t)=√{square root over (I ² +Q ²)}=√{square root over((I+jQ)×(I+jQ)*)}  (15)

Let the weak signal of interest be denoted by S_(w)(t)=I_(w)+jQ_(w).Additionally, let the strong interference source be denoted byS_(I)(t)=I_(I)+jQ_(I). Additionally, let the noise in the receiversystem be denoted by n(t)=n_(I)+jn_(q).

The received signal can be expressed as the sumS(t)=S_(w)(t)+S_(I)(t)+n(t). Therefore, the composite amplitude A(t) ofS(t) can be written as:

A(t)=√{square root over ((I _(I) +I _(w) +n _(I))²+(Q _(I) +Q _(w) +n_(Q))²)}  (16)

Notice that Equation 16 can be rewritten in terms of componentamplitudes as:

A(t)=√{square root over (A _(I) ² +A _(w) ² +A _(n) ²+2(I _(w) I _(I) +I_(I) n _(I) +I _(w) n _(I))+2(I _(w) I _(I) +I _(I) n _(I) +I _(w) n_(I)))}   (17).

Here, A_(I) corresponds to the amplitude of the interference signal,which can be strong relative to the amplitude A_(w) of the desiredsignal, and A_(n) corresponds to the noise amplitude. In the case wherethe amplitude of the interference signal is significantly greater thanthe amplitudes of the noise or the desired signal, an approximation forA(t) can be expressed as:

A(t)≅√{square root over (A _(I) ²)}=|A _(I)|  (18)

For the case of N constant envelope Binary Phase Shift Keying (BPSK)interference signals, each having a constant envelope A_(i) where i=1, .. . N, the composite envelope (amplitude) can be expressed as:

A _(i)=√{square root over ((Σ_(i=1) ^(N) A _(i) C _(i)(t)e ^(jθ) ^(i)^((t)))(Σ_(i=1) ^(N) A _(i) C _(i)(t)e ^(−jθ) ^(i) ^((t))))}  (19)

where Re²(C_(i)(t))+Im²(C_(i)(t))=1 for the general case of constantenvelope phase shift keying. While the present circuits and methodssuitably can be used for interference signals that use BPSK modulatedsymbols, the present circuits and methods also can be used incircumstances in which the received signal has a finite number ofamplitude levels over the averaging period of the filters (1-N).

Without loss of generality, consider the case for two BPSK interferencesignals. In that case, C_(i)(t)=±1, for i=1,2 and

A _(I)=√{square root over (A ₁ ² +A ₂ ²+2A ₁ A ₂ C ₁(t)C₂(t)cos(φ₁(t)−φ₂(t)))}  (20)

In this case, the amplitude is no longer constant and can assume twodiscrete values as long as φ₁(t)−φ₂(t) is approximately equal to φ₀,where φ₀ is approximately constant over the time in which interferencesuppression processing is taking place. For example, φ₀ in a receivercan be a function of the Doppler offset between the receiver's carrierfrequency and the incoming frequency plus some constant phase term,which can be denoted by Δω_(i). Let θ_(i) be an arbitrary phase offset.The difference φ₁(t)−φ₂(t) can be expressed as:

Δφ=φ₁(t)−φ₂(t)=Δω₁ t−Δω ₂ t+θ ₁−θ₂  (21)

Take for example the case of two 1.023 Mchip/sec BPSK interferencesignals having Doppler frequency offsets of Δω₁ and Δω₂. Defineθ₁−θ₂=Δθ₀. Then,

cos(φ₁(t)−φ₂(t))=cos((Δω₁−Δω₂)t+Δθ ₀)  (22)

should be approximately constant over the period in which the averageamplitude is determined. Without loss of generality, let Δθ₀=0.

Letting

${{\Delta \; f} = \frac{\left( {{\Delta\omega}_{1} - {\Delta\omega}_{2}} \right)}{2\pi}},$

equation 20 then can be rewritten as:

A _(I)=√{square root over (A ₁ ² +A ₂ ²+2A ₁ A ₂ C ₁(t)C₂(t)cos(Δft))}  (23)

As noted above, C_(i)(t)=±1. As a result, it can be understood thatthere are two distinct amplitude levels for two interference signals, solong as cos(Δft) is approximately constant over the averaging period(e.g., sliding window of samples used to determine the average (mean)value of the interference).

Similarly, for three interference signals, the composite amplitude A_(I)of the interference signal can be expressed as:

$\begin{matrix}{A_{1} = \sqrt{\begin{matrix}{A_{1}^{2} + A_{2}^{2} + A_{3}^{2} + {2\; A_{1}A_{2}{C_{1}(t)}{C_{2}(t)}{\cos \left( {\Delta \; f_{12}t} \right)}} +} \\{{2\; A_{2}A_{3}{C_{2}(t)}{C_{3}(t)}{\cos \left( {\Delta \; f_{23}t} \right)}} + {2\; A_{1}A_{3}{C_{1}(t)}{C_{3}(t)}{\cos \left( {\Delta \; f_{13}t} \right)}}}\end{matrix}}} & (24)\end{matrix}$

Table 1 lists the code states used to determine possible amplitudevalues for three signals. Equation 24 above shows that there are threeterms which depend on the sign of the terms C₁(t), C₂(t), and C₃(t), andwhich will contribute to the composite amplitude. Denoting the compositeamplitude levels as L₀ . . . L₃, it can be seen from Table 1 that thereare 4 distinct composite amplitude levels as a result of combining thethree sign-dependent terms.

TABLE 1 C₁(t)C₂(t), C₂(t)C₃(t), C₁(t) C₂(t) C₃(t) C₃(t)C₁(t) AmplitudeLevel 1 1 1 1, 1, 1 L₀ 1 1 −1 1, −1, −1 L₁ 1 −1 1 −1, −1, 1 L₂ 1 −1 −1−1, 1, −1 L₃ −1 1 1 −1, 1, −1 L₃ −1 1 −1 −1, −1, 1 L₂ −1 −1 1 1, −1, −1L₁ −1 −1 −1 1, 1, 1 L₀

Notice that there are four unique possibilities for three interferencesignals, corresponding to a maximum of four unique amplitude values.Similarly, with four interferers, such as shown in FIG. 5C, there are amaximum of eight possible amplitude levels. In general, M interferencesignals can generate up to N=2^(M-1) possible amplitudes. As onenonlimiting example, to apply the present circuits and methods to areceived signal that includes six interference signals, 32 amplitudefilters (mean estimation circuits) can be used.

Some embodiments of the present circuits and methods can include use ofN simultaneous amplitude estimation circuits. For example, clusterdefinition circuit 521 illustrated in FIG. 5A or the circuit illustratedin FIG. 5D can include N amplitude estimation circuits, such as FIR orIIR filters, configured to define respective amplitude clusters based onthe values of the last F_(s)*T_(i) amplitude samples, where F_(s)corresponds to the sample rate of the filter and T_(i) corresponds tothe window length (in time) over which the filter is determining theamplitude value. As one example, the following FIR filter can be usedfor each amplitude estimation circuit:

$\begin{matrix}{y_{k} = {\frac{1}{F_{s}T_{i}}{\sum\limits_{n = 1}^{F_{s}T_{i}}\; x_{k - n}}}} & (25)\end{matrix}$

Note, however, that other FIR filters suitably can be used. As anotherexample, an IIR filter can be used, such as:

y _(k+1) =δx _(k)+(1−δ)y _(k)  (26)

where δ corresponds to a parameter selected based on the desirableresponse time of the filter, e.g., in the case of an IIR filter, theapproximate time over which the estimate is being performed.

In some embodiments, the present circuits and methods suitably can beimplemented as an appliqué, signal processing circuit, or algorithm in aradio frequency receiver. For example, FIGS. 5E-5F schematicallyillustrate exemplary appliqué implementations for reducing aninterference signal that spectrally overlaps a desired signal based onclustering the amplitudes of the signals, according to some embodimentsof the present invention. In the implementations illustrated in FIG.5E-5F, the processor reduces the interference power to signal ratio(I/S).

In the appliqué implementation illustrated in FIG. 5E, the receivedradio frequency (RF) signal, S_(w)(t), is corrupted by interferenceS_(I)(t). The composite signal is received at an antenna, amplified by alow noise amplifier (LNA), and then translated to an intermediatefrequency (IF) using a downconverter where it is sampled by ananalog-to-digital converter (ADC) and digitally converted to an in-phase(I) and quadrature (Q) baseband signal inside of the processor. Thein-phase and quadrature signals are processed by the processor tosuppress the interference signal, e.g., in accordance with method 500described above with reference to FIG. 5B. After passing through theprocessor, the processed in-phase and quadrature baseband signals areconverted back to an IF carrier where they are converted to analogsignals before using a digital-to-analog converter (DAC) and translatingthe signals back to RF using an upconverter before they enter an RFreceiver. FIG. 5F illustrates an alternative implementation in which thesignals are converted to and from I/Q (baseband) in the RF domain. Inthis implementation, the I and Q signals are digitized using two ADCs(one for I and one for Q), then processed directly by the processor(e.g., in accordance with method 500 described above with reference toFIG. 5B) without further translation. After passing through theprocessor, the processed I and Q signals are converted to the analogdomain using two DACs. In the implementations illustrated in FIGS.5E-5F, the processor reduces the interference into the receiver, e.g.,transforms a high I/S ratio to a low I/S ratio. In some embodiments, aprocessing device in the receiver can be used so as to avoid the needfor a separate DAC and upconversion circuit following the processor. Insuch a case, the receiver's ADC, LNA, and downconverter can be used. Theprocessor illustrated in FIGS. 5E-5F can include the receiver's existingprocessor, or an additional processing device connected to apre-existing receiver processor. In such embodiments, a DAC may notnecessarily be needed.

The signal receiver can include a global navigation satellite systemreceiver (GNSS) such as GPS, Glonass, Compass, or Galileo, or a cellularwireless communications receiver, WiFi, Bluetooth, or other radiofrequency receiver. For example, the present circuits and methods can beapplied to radar receivers or satellite communication system receivers.

In some embodiments, the present circuits and methods suitably can beimplemented using a digital processor. Devices in the receiver capableof performing some or all actions of the processor illustrated in FIGS.5E-5F or the circuits illustrated in FIGS. 5A and 5D can include a fieldprogrammable gate array (FPGA), application specific integrated circuit(ASIC), central processor unit (CPU), graphics processor unit (GPU), orother similar digital processing device. Alternatively, the presentcircuits and methods suitably can be implemented using an analogprocessor.

FIG. 5G schematically illustrates selected components of anotherexemplary interference suppression circuit for use in reducing aninterference signal that spectrally overlaps a desired signal based onbased on clustering the amplitudes of the signals, according to someembodiments of the present invention. In the embodiment illustrated inFIG. 5G, the multi-level amplitude estimation circuit (estimator)includes a bank of amplitude estimation filters, and the decisioncircuit computes the minimum distance to each cluster so as to decidewhether or not interference suppression should take place for a currentsample. It also compares the value of the current sample's amplitudewith a threshold so as to determine whether the interference to noiselevel is sufficiently high that suppression is desirable. Note that theembodiment illustrated in FIG. 5G (as well as other embodiments providedherein) also can suppress multiple non-constant envelope interferencesignals having a finite number of amplitude levels over the averagingperiod, as well as multi-leveled QAM, ASK, or other multi-leveledinterference signals.

Note that the present circuits and methods further can be used tosuppress interference signals having impulsive interference, such asnon-ideal pulses (sudden spikes or dips) or pulsed interference orinterference that changes faster than the averaging period. For example,based upon a given interference amplitude sample being less than asecond threshold TH2, the sample amplitude may not be suppressed and theamplitude value may not be assigned to a cluster (e.g., may not enterone of the N-averaging filters). This can inhibit pulsed interferencefrom degrading the average for a given cluster and from causing theinterference suppression to fail or lose effectiveness. The thresholdTH2 can be set as a function of the interference to noise ratio orquantity or in a manner analogous to that described in greater detailabove. As is shown FIG. 5G, if the given interference amplitude sampleis less than TH2, it can be sent directly to the output of thesuppression algorithm unprocessed. In the embodiment shown in FIG. 5G,subtracting zero from the input amplitude sample passes that sample tothe output as the amplitude residual. The first threshold illustrated inFIG. 5G, TH1, can inhibit rapid amplitude changes (much faster than thefilter averaging period) from causing errors in the cluster estimate forthe mean value of the constant level. Then based upon the minimumdistance exceeding the first threshold, TH1, the amplitude residualvalue associated with that minimum distance can be set to zero or othersuitable constant, and the interference suppression operation (e.g.,subtraction of A_(sm) in FIG. 5G) is not performed. In some embodiments,halting the interference suppression operation can be achieved bysubtracting the input amplitude from itself, for the correspondingamplitude sample in which the minimum distance d_(min) exceeds thesecond threshold, such that the output amplitude residual will be zerofor that corresponding amplitude sample. In some embodiments, inaddition to halting the interference suppression operation, none of thefilters are updated when TH1 is exceeded.

Accordingly, in some embodiments, whenever TH1 is exceeded by theminimum distance or the incoming amplitude sample is less than TH2, thefilters are not updated. As a result of such thresholding and the factthat only one of the N filters is updated each sample, the filter'seffective sampling rate can be lower than the sampling rate of theincoming amplitude samples. In other words, in some embodiments, thefilters can be discontinuously sampled.

Note that for clarity of representation, FIG. 5G does not show delaylines that can be provided in a hardware or software implementation soas to properly time-align the amplitude samples, amplitude estimates(cluster definitions), and phase samples. In some embodiments, thedecision making block and the filters can incur some fixed amount oftime when implemented, and the phase samples can be delayed to match.Additionally, the amplitude samples subtracted from the amplitudeestimates also can be pipelined before reaching the summation block soas to allow time for the proper estimate to appear at the summation.

Additionally, note that the designations “first” and “second” thresholdsherein—with regards to these and other embodiments—do not require orimply a particular order of operation.

FIG. 5H schematically illustrates selected components of anotherexemplary interference suppression circuit for use in reducing aninterference signal that spectrally overlaps a desired signal based onbased on clustering the amplitudes of the signals, according to someembodiments of the present invention. The implementation illustrated inFIG. 5H excludes the use of thresholding. Again, for clarity ofrepresentation, delay lines for time-alignment are not illustrated. Notethat the filters illustrated in FIGS. 5G-5H can be configured so as toinclude an adaptable integration window (time period over whichaveraging takes place) so as to be adaptable to multiple interferencesources that may, in some cases, be constant only over short periods oftime.

FIG. 5I illustrates steps in an exemplary method for initializingamplitude cluster values, according to some embodiments of the presentinvention. Method 510 illustrated in FIG. 5I includes computing ahistogram of an input sample record of length L (511); taking aderivative of histogram values (512); determining zero crossings (513),and determining cluster initial values from the detected zerocrossing(s) (514). Method 510 illustrated in FIG. 5I can determine theinitial cluster values (possible amplitude values) for a given sampleset. One possible implementation of method 510 includes computing thehistogram of the prior L samples, for example, L=512 or other suitablevalue.

Note that L can be adapted based on the measured signal to noise ratiobased on an LMS algorithm or other suitable technique. Alternatively, Lcan be a fixed quantity. For example, for a relatively rapidly varyinginterference signal, L can be smaller than for a more slowly varyinginterference signal. Additionally, for lower values of interference tosignal ratio (I/S), L can be selected to be longer. Alternatively,multiple histogram values (e.g., three) can be computed and average. Inan exemplary embodiment, the histogram values can be averaged by asliding window average using a digital filter. In one example, anexample implementation uses the following FIR filter:

y _(k)=0.2x _(k−1)+0.2x _(k−2)+0.2x _(k−3)+0.2x _(k−4)+0.2x _(k−5)  (27)

In the embodiment illustrated in FIG. 5I, after the histogram isdetermined (step 511), the derivative of the histogram is computed (step512). After the derivative is computed, the zero-crossings enumerate thenumber and value of each initial amplitude cluster (steps 513 and 514).FIG. 5J illustrates an example of output of cluster initializationmethod 510 illustrated in FIG. 5I, according to some embodiments of thepresent invention. Note that the green curve in FIG. 5J represents theaveraged histogram, the blue curve is the histogram before averaging,the red curve is the estimated derivative of the histogram, and the cyancurve indicated detected histogram peaks that will be loaded into thecluster initializer.

Note that in environments where the nature of the interference signalcan be rapidly changing, it can be useful to periodically initialize theclusters (e.g., in accordance with method 510 illustrated in FIG. 5I) soas to account for potential changes in amplitude distribution.

In some embodiments, a non-adaptive k-means technique or an adaptivek-means technique can be used to define clusters, e.g., by clusterdefinition circuit 521 illustrated in FIG. 5A or during step 502 ofmethod 500 illustrated in FIG. 5B, or to decide to which cluster a givenamplitude sample is to be assigned, e.g., by cluster assignment circuit522 illustrated in FIG. 5A or during step 503 of method 500 illustratedin FIG. 5B. In a non-adaptive k-means implementation, there may in somecircumstances be only a fixed number of clusters to which an amplitudesample can be assigned. As such, if a new amplitude sample is far fromthe existing clusters' amplitudes, then in a non-adaptive k-meanstechnique, the incoming amplitude sample can be thresholded (e.g.,ignored) or assigned to the nearest cluster. Additionally, in some realworld environments in which each interference signal has a nonzeroDoppler frequency, the multiple amplitude levels seen in amultiple-interferer scenario can change over time, which means thateventually k-means clusters that track such amplitudes can becomerelatively close to one another, e.g., close enough potentially towarrant defining a cluster in which two or more previous clusters aremerged with one another. Or, as multiple amplitude levels move apartfrom one another, it potentially can be useful to define clusters thattrack a diverging amplitude level.

One exemplary method of allowing a k-means technique to support multipleclusters is to continuously send estimates (which in some embodimentscan be obtained via histogram, such as described above with reference toFIGS. 5I-5J) to the cluster definition circuitry, e.g., to the clusterfilters. Such estimates can include both an estimate of the number ofclusters and the approximate cluster amplitude location.

An alternative implementation can be to allow the number of clusters tobe adaptive based on measurements of the “inter-cluster distances.”Clusters can be added, destroyed, or merged based on the incoming signalamplitude, the available number of clusters, and the distance betweenclusters. For example, in some embodiments, a circuit can be configuredso as to accommodate up to a maximum number of clusters. An“inter-cluster distance” can be defined to be the distance between anypair of clusters. If any two cluster's distance from one another (anyinter-cluster distance) is below a threshold, e.g., if the two clustersare sufficiently close to one another, it can be useful to merge thosetwo clusters into a single cluster. For example, such merging can helpin averaging small errors, as well as freeing up resources so that thecircuit can define and assign amplitude samples up to the maximum numberof clusters using relatively large inter-cluster distances.

FIG. 5K illustrates an exemplary method of merging amplitude clusters,according to some embodiments of the present invention. Method 530illustrated in FIG. 5K suitably can be used, e.g., by cluster definitioncircuit 521 illustrated in FIG. 5A or during implementation of step 502of method 500 illustrated in FIG. 5B, so as to update the clusterdefinitions before, during, or after assigning amplitude samples to suchclusters. For example, in some embodiments, a circuit can be configuredso as to define up to a maximum number of clusters, but the circuit mayuse less than that maximum number. The circuit may have initialized acertain number of amplitude clusters (e.g., filters) using a histogramin a manner such as described above with reference to FIGS. 5I-5J, orany other suitable manner. Method 530 illustrated in FIG. 5K can includemeasuring the inter-cluster distances between all active clusters (531),e.g., at a defined time interval. Method 530 includes determiningwhether any two clusters are measured to have an inter-cluster distancethat is less than a threshold T3 (532), e.g., by comparing each of themeasured inter-cluster distances to threshold T3. Method 530 alsoincludes, based upon any two clusters being measured to have aninter-cluster distance that is less than a threshold T3, merging the twoclusters by averaging their values (amplitudes) and deleting one of thetwo clusters (533). The new amplitude value of the merged clusters canbe written into the non-deleted cluster. Method 520 also includesupdating the number of active clusters in use (534), e.g., updating thecircuit's count of the number of active clusters.

Additionally, or alternatively, in some embodiments, new clusters can beadded based upon the incoming amplitude sample's distance to allexisting clusters being above a certain threshold. For example, FIG. 5Lillustrates an exemplary method of adding new amplitude clusters,according to some embodiments of the present invention. Method 540illustrated in FIG. 5L suitably can be used, e.g., by cluster definitioncircuit 521 illustrated in FIG. 5A or during implementation of step 502of method 500 illustrated in FIG. 5B, so as to update the clusterdefinitions before, during, or after assigning amplitude samples to suchclusters. For example, in some embodiments, a circuit can be configuredso as to define up to a maximum number of clusters, but the circuit mayuse less than that maximum number. The circuit may have initialized acertain number of amplitude clusters (e.g., filters) using a histogramin a manner such as described above with reference to FIGS. 5I-5J, orany other suitable manner. Method 540 illustrated in FIG. 5L can includemeasuring the distance of the incoming amplitude sample to each cluster(541). Method 540 includes determining whether the smallest of thosemeasured distances exceeds a threshold T4 (542), e.g., by comparing eachof the measured distances to threshold T4. Method 540 also includes,based upon the minimum distance (smallest of the measured distances)exceeding the threshold T4, further determining whether the number ofactive clusters are less than the maximum number of clusters (543).Method 540 also includes, based upon the minimum distance not exceedingthreshold T4 or based upon the number of clusters not being less thanthe maximum, assigning (inputting) the amplitude sample to the clusterassociated with the smallest minimum distance (546). Method 540 alsoincludes, based upon the number of active clusters being less than themaximum number of clusters, adding a new cluster with an initial value(amplitude) set to any suitable value, e.g., set to the amplitude of theincoming sample (544). Method 540 also includes updating the number ofactive clusters in use (545), e.g., updating the circuit's count of thenumber of active clusters.

Note that in embodiments such as described herein with reference toFIGS. 5K-5L, the thresholds T3 (for merging clusters) and T4 (for addingclusters) optionally can be determined adaptively, e.g., by continuouslymonitoring the maximum amplitude of the received signal. For example,the circuit can measure the maximum amplitude seen over the past Nsamples of the received signal, and can divide that maximum by a setthreshold T3 d or T4 d, which respectively can produce the threshold T3or T4.

Accordingly, in some embodiments of an “adaptive k-means” approach, thenumber of clusters can vary over time, e.g., based upon input rules ofinter-cluster distance, maximum allowed distance of each incomingamplitude sample to existing clusters, and the maximum number ofavailable clusters. Such rules are intended to be merely exemplary of anadaptive implementation, and are not intended to be limiting. Forexample, alternative methods and circuits can be used so as to provide adecision mechanism for assigning an incoming amplitude sample A_(k) toan amplitude cluster. For example, a k-means based circuit or method canmake such a decision based upon the minimum distance between clustersand an amplitude sample, or other similar criterion. Other decisionssuitably can be implemented, optionally without initializing clusters.

In one such alternative implementation, the circuits and methods can usebinned clusters in which a fixed number of clusters initially aredefined having amplitudes that span the available amplitude spacerelatively evenly. Alternatively, clusters can be excluded from thelower values of the amplitude space, e.g., at I/S levels below which theprocessing gain of the received signal can be adequate to mitigateinterference). In some embodiments, each cluster averages amplitudesamples received in a “bin” of amplitude samples, and the clusterdefinition circuitry (e.g., cluster filter) output may not necessarilymove beyond its fixed bin. The incoming signal sample (which can includeamplitude, amplitude squared, or some other value of a given domain) canbe rounded to the minimum bin size so as to determine to which clusterthe incoming sample is to be assigned (injected). The unrounded (fullprecision) sample then is sent to that cluster, and the average can beupdated.

Note that in some embodiments of such binned implementations, there canbe a fixed number of clusters that suitably span the available amplitudespace, e.g., are spaced linearly or nonlinearly relative to one another.In some embodiments, only signal samples that are within the bin limitsof a cluster contribute to the output, e.g., filtered output, of thatcluster. For illustration, assume that the binned cluster approach isused, with linearly spaced bins. Assume that A_(max) is the maximumamplitude expected in the incoming signal. The minimum amplitudepartition size can be denoted as “minsize.” The entire availableamplitude space can be quantized into N clusters, where the startingvalues of the clusters can be expressed as:

Initial_values=0,1*minsize,2*minsize,3*minsize, . . . A _(max)  (28)

In one example, a decision of where to assign an incoming amplitudesample to one of the N available clusters can be based upon a roundingprocess in which the incoming amplitude sample A_(in) is quantized tothese partitions to obtain a pointer to a cluster filter, as can beexpressed by:

Pointer=round(A _(in)*minsize)  (29)

This pointer can take a value 0, 1, 2, . . . , N, e.g., can point to oneof the N available clusters, e.g., cluster filters. The input amplitudesample A_(in) (full precision) can be assigned to that cluster, e.g.,cluster filter, and the output of the can be updated. In such a manner,each cluster, e.g., cluster filter, can receive only values seen withina given amplitude partition space. Based upon an incoming amplitudesample crossing a partition boundary, that sample can be assigned to anappropriate one of the adjacent clusters, and that cluster's average canbe updated. As such, each amplitude cluster can be considered to beconstrained within a corresponding bin. The amplitude space can besliced into bins, and an incoming amplitude sample can be considered tobe assigned to a given cluster by an amplitude slicer. For example, FIG.5M illustrates steps in an exemplary method for initializing andupdating amplitude cluster values, according to some embodiments of thepresent invention. Method 550 illustrated in FIG. 5M includespartitioning the amplitude space, e.g., by defining N+1 clusters seededwith initial values of 0, minsize, . . . maxsize (551), e.g., asperformed by cluster definition circuit 521 illustrated in FIG. 5A orstep 502 of method 500 illustrated in FIG. 5B. Method 550 illustrated inFIG. 5M also includes finding the closest bin, e.g., determining P=round(A_(in)/minsize) (552), e.g., as performed by cluster assignment circuit522 illustrated in FIG. 5A or step 503 of method 500 illustrated in FIG.5B. Method 550 illustrated in FIG. 5M also includes injecting(assigning) the incoming amplitude sample A_(in) into the cluster filterpointed to by P, and updating that cluster's filter (553), e.g., asperformed by cluster assignment circuit 522 illustrated in FIG. 5A orstep 503 of method 500 illustrated in FIG. 5B. Steps 552 and 553 can berepeated any suitable number of times for new incoming amplitudesamples.

In some embodiments, circuits and methods based on binned clusters canassign an incoming sample to an available cluster based on rounding theamplitude sample and assigning it to the nearest cluster. In someembodiments, it can be useful to select an appropriate bin size. Forexample, a bin size that maximizes output C/No can be based on the J/Sratio of the interference signal. FIG. 5N illustrates the simulated C/Nofor different sizes of bins in a binned cluster implementation,according to some embodiments of the present invention. A simulation wasrun in which different bin sizes were used for varying J/S ratios for abinned clusters based method in which the received signal included fourunfiltered BPSK matched spectral interference signals, each spaced 1 kHzapart in Doppler frequency. It can be understood from FIG. 5N that for aJ/S of 60 dB, the optimum number of binned clusters is about 100,whereas at a J/S of 50 dB, it can be useful to reduce the number ofbinned clusters to about 50.

It should be appreciated by one of skill in the art that alternativeembodiments of multi-level interference mitigation based on clusteringin either k-means, adaptive k-means, binned clusters or any clusteringapproach described herein may be implemented clustering based onreceived power or amplitude to a nonlinear power. The techniques toidentify and process signals based on amplitude clusters would bereplaced with techniques to identify and process signals based on powerclusters or cluster of amplitude values to a nonlinear power.

Note that in some embodiments, the number of bins available for circuitsand methods based on binned clusters optionally can be adapted in realtime, e.g., by measuring the maximum amplitude of the input signal everyM samples, where M corresponds to the number of samples used todetermine A_(max). In some embodiments, the maximum amplitude ismeasured and the bin size is adjusted every M samples. In someembodiments, such an adjustment can be made, for example, by dividingthe maximum amplitude seen by a number obtained from a look-up tablethat has been pre-loaded in such a manner that the number of binsavailable for a given amplitude maximizes the C/No. The number of binscan be adaptively selected based on the measured interference to noiselevel (e.g., in an appliqué configuration), measured C/No, a combinationof the measured C/No and the measured I/S, or any other suitable metricor combination of metrics. Illustratively, an LMS or similar algorithmcan be used for such adaptive implementations.

Accordingly, some embodiments of the present circuits and methods canprovide a single-antenna technique that can suppress non-constantenvelope (amplitude) interference signals having multiple levels andthat spectrally overlap or are spectrally matched to a desired signal.In some embodiments, estimation of multiple amplitude levels in theamplitude domain (or non-linear amplitude domain(s)) can be used tomitigate an interference signal that has rapid amplitude variations.Illustratively, the present circuits and methods can be implemented asan appliqué and rapidly fielded with an existing system or built intoreceiver boards with an additional chip, or integrated into futureASICs. The approach can be applicable to GPS and other satellitenavigation signals, radar receivers, satellite communications,commercial wireless, WiFi, and other signaling standards includingBluetooth and cellular signals.

FIG. 5O illustrates the simulation performance of 3 nonlimiting,exemplary embodiments of the present invention. A simulation was runwith 4 matched spectral BPSK interference signals, each separated inDoppler frequency, which were added to the desired signal (in this case,a simulated GPS C/A code signal) and noise. In the simulation the BPSKinterference signals were at least 1 kHz apart from each other inDoppler frequency. Three nonlimiting, exemplary embodiments of thepresent circuits and methods were simulated, along with a simulation ofan unprotected receiver. The resulting C/A code C/No after interferencesuppression is plotted in FIG. 5O for three nonlimiting, exemplaryembodiments of the invention. The trace in FIG. 5O labelled “k-means”corresponds to an exemplary implementation where a fixed number ofclusters are initially chosen and the average cluster amplitude valuesare updated every sample based on the average of the samples assigned tothat cluster at that time. The trace in FIG. 5O labelled “adaptivek-means” corresponds to a simulation where the number of clusters arenot fixed, but instead new clusters can be added over time, andadditionally clusters can be merged, as previously described. The tracelabelled “binned clusters” corresponds to a simulation where the “binnedcluster” approach as previously described is used to reduce theinterference. It can be seen from FIG. 5O that all three simulatedembodiments show an advantage over the unprotected simulation aboveabout J/S=40 dB.

Alternative Embodiments

It should be appreciated that the present circuits and methods suitablycan be implemented so as to reduce the effects of interference in anypractical application. As an example application, the present circuitsand methods can provide an advantage as compared to cognitive radio.Suppose there are two co-channel signals. If one signal is much strongerthan the other, then the strong signal is typically easy to detect anddemodulate, but the weaker signal can be lost in the interferencewithout appropriate remediation. For this reason, cognitive radios seekunoccupied parts of the spectrum. The present circuits and methods canwork alone, or as a supplement to cognitive radio, by reducinginterference at the receiver. This can allow more signals to share thespectrum and provide the opportunity to use whatever portion of thespectrum is needed whenever it is needed.

Other exemplary practical applications that can benefit from the presentcircuits and methods include, but are not limited to, the following:

Satellite communications, in which the present circuits and methods canfacilitate suppression of a wide variety of common interference signals,and can protect SATCOM from local interference;

Mitigating intentional or unintentional interference to satellitenavigation receivers including but not limited to GPS receivers, Glonassreceivers, Galileo receivers, compass receivers and hybrid satellitenavigation. For example, GPS privacy jammers have become a growingconcern.

Commercial wireless communications including wireless CDMA andshort-range communications such as Bluetooth receivers, that muchoperate in increasingly interference rich environments.

LPI (low probability of intercept) and LPD (low probability ofdetection) communications, in which the present circuits and methods canfacilitate hiding weak desired signals under strong signals such thatonly authorized users readily can find the weak desired signals; or moregenerally

Anti jam receivers, in which the present circuits and methods canfacilitate resistance to a wide variety of potential jamming sources,whether such sources are intentional or unintentional, includingconsumer goods that can radiate unauthorized energy into criticalmilitary use bands.

While various illustrative embodiments of the invention are describedabove, it will be apparent to one skilled in the art that variouschanges and modifications can be made therein without departing from theinvention. For example, interference reduction circuit 100 can beconfigured to work with, and to be coupled to, a pre-existing receiver10 or interference suppression appliqué 10′, but need not necessarily beconsidered to be an integral part of such a receiver or interferencesuppression appliqué, and indeed suitably can be used with any circuitrythat would benefit from interference reduction. The appended claims areintended to cover all such changes and modifications that fall withinthe true spirit and scope of the invention.

1. A method for processing a received signal, the received signalincluding a desired signal and an interference signal that spectrallyoverlaps the desired signal, the method comprising: obtaining anamplitude of the received signal; obtaining an average amplitude of thereceived signal based on at least one prior amplitude of the receivedsignal; subtracting the amplitude from the average amplitude to obtainan amplitude residual; and based upon an absolute value of the amplituderesidual being less than or equal to a first threshold, inputting thereceived signal into an interference suppression algorithm so as togenerate a first output including the desired signal with reducedcontribution from the interference signal; wherein the interferencesignal originates from a source different from the desired signal. 2.The method of claim 1, further comprising bypassing the interferencesuppression algorithm based upon the absolute value of the amplituderesidual being greater than the first threshold.
 3. The method of claim2, further comprising, based upon bypassing the interference suppressionalgorithm, generating a second output equal to a predetermined value. 4.The method of claim 1, further comprising bypassing the interferencesuppression algorithm based upon the absolute value of the amplitudebeing less than a second threshold.
 5. The method of claim 1, furthercomprising bypassing the interference suppression algorithm based upon apower of the received signal being less than a second threshold.
 6. Themethod of claim 1, further comprising bypassing the interferencesuppression algorithm based upon an interference to noise ratio of thereceived signal being less than a second threshold.
 7. The method ofclaim 4, further comprising, based upon bypassing the interferencesuppression algorithm, generating a second output equal to the receivedsignal.
 8. The method of claim 1, wherein the first threshold is fixed.9. The method of claim 1, wherein the first threshold varies as afunction of the amplitude.
 10. The method of claim 1, wherein thereceived signal includes a digitized time domain signal, wherein theamplitude is that of a first sample of the digitized time domain signal,and wherein the average amplitude is an average of the amplitudes of aplurality of samples of the digitized time domain signal.
 11. The methodof claim 1, further comprising: obtaining a phase of the receivedsignal; and constructing an output based on the phase and the firstoutput.
 12. The method of claim 1, wherein the interference suppressionalgorithm operates in an I/Q time domain of the received signal, in afrequency domain of the received signal, in an amplitude domain of thereceived signal, in a nonlinear amplitude domain of the received signal,or in a combination of more than one domain of the received signal. 13.A circuit for processing a received signal, the received signalincluding a desired signal and an interference signal that spectrallyoverlaps the desired signal, the circuit comprising: an amplitudecircuit configured to: obtain an amplitude of the received signal;obtain an average amplitude of the received signal based on at least oneprior amplitude of the received signal; and subtract the amplitude fromthe average amplitude to obtain an amplitude residual; and an arithmeticcircuit configured to, based upon an absolute value of the amplituderesidual being less than or equal to a first threshold, input thereceived signal into an interference suppression algorithm so as togenerate a first output including the desired signal with reducedcontribution from the interference signal; wherein the interferencesignal originates from a source different from the desired signal. 14.The circuit of claim 13, wherein the arithmetic circuit further isconfigured to bypass the interference suppression algorithm based uponthe absolute value of the amplitude residual being greater than thefirst threshold.
 15. The circuit of claim 14, wherein the arithmeticcircuit further is configured, based upon bypassing the interferencesuppression algorithm, to generate a second output equal to apredetermined value.
 16. The circuit of claim 13, wherein the arithmeticcircuit further is configured to bypass the interference suppressionalgorithm based upon the absolute value of the amplitude being less thana second threshold.
 17. The circuit of claim 13, wherein the arithmeticcircuit further is configured to bypass the interference suppressionalgorithm based upon a power of the received signal being less than asecond threshold.
 18. The circuit of claim 13, wherein the arithmeticcircuit further is configured to bypass the interference suppressionalgorithm based upon an interference to noise ratio of the receivedsignal being less than a second threshold.
 19. The circuit of claim 16,wherein the arithmetic circuit further is configured, based uponbypassing the interference suppression algorithm, to generate a secondoutput equal to the amplitude of the received signal.
 20. The circuit ofclaim 13, wherein the first threshold is fixed.
 21. The circuit of claim13, wherein the first threshold varies as a function of the firstamplitude.
 22. The circuit of claim 13, wherein the received signalincludes a digitized time domain signal, wherein the amplitude is thatof a first sample of the digitized time domain signal, and wherein theaverage amplitude is an average of the amplitudes of a plurality ofsamples of the digitized time domain signal.
 23. The circuit of claim13, wherein the amplitude circuit further is configured to obtain aphase of the received signal; and the circuit further including a signalconstruction circuit coupled to the amplitude circuit and to thearithmetic circuit, the signal construction circuit being configured toconstruct an output based on the phase and the first output.
 24. Thecircuit of claim 13, wherein the interference suppression algorithmoperates in an I/Q time domain of the received signal, in a frequencydomain of the received signal, in an amplitude domain of the receivedsignal, in a nonlinear amplitude domain of the received signal, or inmore than one domain of the received signal. 25-108. (canceled)